-----------------------------------------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\tabi\Dropbox\BOMO\JEPSReplication\FinalReplication\Final\log.log
  log type:  text
 opened on:  24 Jan 2018, 11:52:31

. 
. *** Import and process data from the nationally representative survey.
. do "Study1_CleanUp.do"

. /// This file cleans up the data downloaded from Qualtrics.
> 
. use Study1_raw.dta, clear

. 
. *** Drop observations of individuals who did the survey too quickly or took too long.
. keep if q_totalduration > 336
(332 observations deleted)

. keep if q_totalduration < 1993
(118 observations deleted)

. 
. *** Rename Treatement Variables 
. g treatment = 1 if t_control_1 == 1
(1,627 missing values generated)

. replace treatment = 2 if t_security_1 == 1
(339 real changes made)

. replace treatment = 3 if t_hr_1 == 1
(299 real changes made)

. replace treatment = 4 if var65 == 1
(348 real changes made)

. replace treatment = 5 if t_imm_1 == 1
(309 real changes made)

. replace treatment = 6 if t_dom_1 == 1
(326 real changes made)

. 
. tab treatment, gen(treatment2)

  treatment |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |        344       17.51       17.51
          2 |        339       17.25       34.76
          3 |        299       15.22       49.97
          4 |        348       17.71       67.68
          5 |        309       15.73       83.41
          6 |        326       16.59      100.00
------------+-----------------------------------
      Total |      1,965      100.00

. 
. *** Create DV Variable
. gen r_imm2 = 1 if r_imm <2
(1,775 missing values generated)

. replace r_imm2 = 0 if r_imm==3
(661 real changes made)

. replace r_imm2 = -1 if r_imm>4
(471 real changes made)

. 
. *** Create Demographic Variables
. gen white = 1 if race == 1
(466 missing values generated)

. replace white = 0 if race > 1
(466 real changes made)

. 
. gen black = 1 if race == 2
(1,816 missing values generated)

. replace black = 0 if race > 2 | race == 1
(1,816 real changes made)

. 
. gen hisp = 1 if race == 3
(1,809 missing values generated)

. replace hisp = 0 if race > 3 | race < 3
(1,809 real changes made)

. 
. gen asian = 1 if race == 4
(1,872 missing values generated)

. replace asian = 0 if race > 4 | race < 4
(1,872 real changes made)

. 
. gen age2 = age*age
(2 missing values generated)

. 
. gen pidnew = 0 if var156 == 1 & pid_strong == 1
(1,688 missing values generated)

. replace pidnew = 1 if var156 == 1 & pid_strong == 0
(260 real changes made)

. replace pidnew = 2 if var156 == 3 & pid_lean == 1
(174 real changes made)

. replace pidnew = 2 if var156 == 4 & pid_lean == 1
(10 real changes made)

. replace pidnew = 3 if var156 == 3 & pid_lean == 0
(395 real changes made)

. replace pidnew = 3 if var156 == 4 & pid_lean == 0
(29 real changes made)

. replace pidnew = 4 if var156 == 3 & pid_lean == -1
(183 real changes made)

. replace pidnew = 4 if var156 == 4 & pid_lean == -1
(7 real changes made)

. replace pidnew = 5 if var156 == 2 & pid_strong == 0
(252 real changes made)

. replace pidnew = 6 if var156 == 2 & pid_strong == 1
(347 real changes made)

. 
. 
. foreach y of varlist treatment22-treatment26{
  2.         gen pid_`y' = pidnew*`y'
  3.         }
(31 missing values generated)
(31 missing values generated)
(31 missing values generated)
(31 missing values generated)
(31 missing values generated)

. 
. gen female = 1-male

. 
. foreach y of varlist treatment22-treatment26{
  2.         gen fem_`y' = female*`y'
  3.         }
(6 missing values generated)
(6 missing values generated)
(6 missing values generated)
(6 missing values generated)
(6 missing values generated)

. 
.         
. **** Isolate Immigration Treatment
. gen rep =1 if pidnew<3
(1,244 missing values generated)

. replace rep = 0 if pidnew >3 & pidnew !=.
(789 real changes made)

. 
. foreach y of varlist treatment22-treatment26{
  2.         gen rep_`y' = rep*`y'
  3.         }
(455 missing values generated)
(455 missing values generated)
(455 missing values generated)
(455 missing values generated)
(455 missing values generated)

.         
. 
. 
. 
. *** DROPPING UNUSED VARIABLES ***
. drop v1 - pid timeloadintro - timeloadtf operation - intro news1 - treat_time_4 ht_man2 - govt_grid_8 ht_time6_1 - jbreader vet - vet_family

. drop born_again - var156 finalq - locationaccuracy

. 
.         
. ***Rescaling variables
. gen concernR = (concern - 1)/4
(7 missing values generated)

. gen problemR = (problem-1)/4
(7 missing values generated)

. gen r_immR = (5-r_imm)/4
(14 missing values generated)

. 
. gen ageR = (age-18)/68
(2 missing values generated)

. gen religiosity = 1 if religion != 5
(513 missing values generated)

. replace religiosity = 0 if religion == 5
(513 real changes made)

. gen incomeR = (income-5)/170
(29 missing values generated)

. gen college = 1 if educ >= 4
(1,004 missing values generated)

. replace college = 0 if educ < 4
(1,004 real changes made)

. 
. 
. *** Generating/Rescaling Variables for Moderation
. gen treat=0 if treatment==1
(1,627 missing values generated)

. replace treat=1 if treatment==5
(309 real changes made)

. gen pidnewR = pidnew/6
(31 missing values generated)

. 
. gen treat_rep = treat*rep
(1,457 missing values generated)

. 
. label var treat_rep "Treatment X Republican"

. 
. 
. save "Study1_Clean.dta", replace
file Study1_Clean.dta saved

. 
end of do-file

. 
. *** Import and process data from the convience sample.
. do "Study2_CleanUp.do"

. ***This file imports the raw survey data and cleans it.
. 
. *** Import the raw data and combine the files
. clear

. insheet using "Study2_raw06102017.csv", comma
(239 vars, 146 obs)

. save "Study2_cleanB.dta", replace
file Study2_cleanB.dta saved

. 
. clear

. insheet using "Study2_raw05042017.csv", comma
(239 vars, 1,051 obs)

. save "Study2_cleanA.dta", replace
file Study2_cleanA.dta saved

. 
. append using "Study2_cleanB.dta", force
(note: variable race_8_text was byte in the using data, but will be str24 now)
(note: variable startdate was str14, now str15 to accommodate using data's values)
(note: variable enddate was str14, now str15 to accommodate using data's values)
(note: variable recordeddate was str14, now str15 to accommodate using data's values)
(note: variable race_9_text was str31, now str35 to accommodate using data's values)

. 
. ***Reformat treatment variables
. gen treat=.
(1,197 missing values generated)

. 
. replace treat=1 if htc==1
(250 real changes made)

. replace treat=2 if ht_con==1 
(242 real changes made)

. replace treat=3 if t_treatleran==1 
(247 real changes made)

. replace treat=4 if treatmor==1
(248 real changes made)

. 
. label variable treat "Treatment Groups"

. label define treat 1 "Control" 2 "Immigration" 3 "Smuggling" 4 "Values" 

. label values treat treat

. 
. *** Rescale dependent variables
. 
. gen wall2 = .
(1,197 missing values generated)

. replace wall2=3 if wall==4
(263 real changes made)

. replace wall2=1 if wall==3
(428 real changes made)

. replace wall2=2 if wall==2
(234 real changes made)

. replace wall2=4 if wall==1
(272 real changes made)

. 
. gen border = (20-htborder)/4

. generate immR = (imm-1)/4

. generate legalR = (legal-1)/3

. generate hawkeyeR = (hawkeye-1)/3

. generate uacR = (uac-1)

. generate wallR = (wall2-1)/3

. generate concernR = (concern-1)/4

. generate problemR = (problem-1)/4

. 
. 
. ***** Clean up Demographics *****
. 
. *** Party identification: Republicans are low end of the scale 
. 
. gen pid7 = .
(1,197 missing values generated)

. replace pid7=1 if pid==1 & pid_strong==1
(216 real changes made)

. replace pid7=2 if pid==1 & pid_strong==2
(233 real changes made)

. replace pid7=3 if pid_lean==1
(98 real changes made)

. replace pid7=4 if pid_lean==3
(90 real changes made)

. replace pid7=5 if pid_lean==2
(95 real changes made)

. replace pid7=6 if pid==2 & pid_strong==2
(193 real changes made)

. replace pid7=7 if pid==2 & pid_strong==1
(272 real changes made)

. 
. 
. label variable pid7 "Seven Point Party Identification"

. label define pid7 3 "Strong Republican" 2 "Weak Republican" 1 "Lean Republican" 0 "Independent" -1 "Lean Democrat" -2 "Weak Democrat" -3 "Strong De
> mocrat"

. label values pid7 pid7

. 
. generate pid7R = (pid7-1)/6

. label variable pid7R "Party Id" 

. 
. drop age

. generate age = 2017 - born

. generate ageR = (age - 18)/88

. label variable ageR "Age"

. 
. generate female = sex

. replace female=0 if sex==3
(3 real changes made)

. label variable female "Female"

. 
. generate incomeR = (income -1)/13

. label variable income "Income"

. 
. generate white = 0

. replace white =1 if race==1
(997 real changes made)

. label variable white "White"

. 
. generate rel = rel_freq - 1
(516 missing values generated)

. replace rel = 0 if (religion ==5 | religion == 8 | religion ==9)
(516 real changes made)

. generate relR = rel/5

. label variable relR "Religious Frequency"

. 
. 
. *** Generate treatment groups by party
. 
. tab treat, gen(treat2)

  Treatment |
     Groups |      Freq.     Percent        Cum.
------------+-----------------------------------
    Control |        250       25.33       25.33
Immigration |        242       24.52       49.85
  Smuggling |        247       25.03       74.87
     Values |        248       25.13      100.00
------------+-----------------------------------
      Total |        987      100.00

. foreach y of varlist treat22-treat24{
  2.         gen pid_`y' = pid7*`y'
  3.         }
(210 missing values generated)
(210 missing values generated)
(210 missing values generated)

. 
. gen rep =1 if pid7<4
(650 missing values generated)

. replace rep = 0 if pid7 >4
(560 real changes made)

. 
. foreach y of varlist treat22-treat24{
  2.         gen rep_`y' = rep*`y'
  3.         }
(285 missing values generated)
(285 missing values generated)
(285 missing values generated)

.         
. drop if treat == .
(210 observations deleted)

. 
. 
. 
. ***DROPPING UNUSED VARIABLES ***
. 
. drop startdate - t_htc_clickcount v31- v34 t_treatlearn_firstclick - t_treatlearn_clickcount t_treatmor_firstclick - t_treatmor_clickcount q119_fir
> stclick - q119_clickcount

. drop t_programs_firstclick - t_programs_clickcount q121_firstclick - q121_clickcount q132_firstclick - q132_clickcount q122_firstclick - man_reform
>  

. drop q123_firstclick - t_gic_clickcount t_percent_firstclick - t_percent_clickcount t_meds_firstclick - t_meds_clickcount t_threat_firstclick - t_t
> hreat_clickcount 

. drop crime_thre - comp q124_firstclick - q124_clickcount q125_firstclick - q125_clickcount q126_firstclick - q126_clickcount q127_firstclick - q128
> _clickcount 

. drop t_screen_firstclick - t_screen_clickcount q129_firstclick - q129_clickcount ft_race_1 - newuser

. 
. 
. *** Generating/Rescaling moderating variables
. 
. gen college = 1 if school >=5
(497 missing values generated)

. replace college = 0 if school <5
(497 real changes made)

. 
. gen trump = 1 if pres == 1
(616 missing values generated)

. replace trump = 0 if pres !=1 & pres !=.
(488 real changes made)

. recode trump (.=0) if vote_2016 == 2
(trump: 126 changes made)

. 
. 
. *** Generate Variable Labels
. set more off

. label var treat22 "Immigration"

. label var treat23 "Smuggling"

. label var treat24 "Values"

. label var ageR "Age"

. label var trump "Voted For Trump"

. label var female "Female"

. label var incomeR "Income"

. label var white "White"

. label var rel "Religiosity"

. label var college "College Degree"

. 
. gen immig_index = (immR+(1-wallR)+uacR+hawkeyeR+legalR)/5

. gen wallR2 = 1-wallR

. 
. label var immR "Immigration Rate"

. label var wallR2 "Mexican Border Wall"

. label var uacR "Unaccompanied Children"

. label var legalR "Path to Citizenship"

. label var hawkeyeR "Illegal Immigration Policy"

. label var immig_index "Immigration Attitudes Index"

. 
. 
. *** Generate Economic Threat & Cultural Threat
. gen econ_threa2 = (7-econ_threa)/6

. gen cultl_thre_v2 = cultl_thre

. replace cultl_thre_v2 = 2 if cultl_thre == 1
(108 real changes made)

. gen cultl_thre2_v2 = (8-cultl_thre_v2)/6

. 
. label var econ_threa2 "Economic Threat"

. label var cultl_thre2_v2 "Cultural Threat"

. 
. *** Generate Ingroup-Centric Beliefs 
. gen outgroupr = (7-outgroup)/6

. gen ingroupr = (7-ingroup)/6

. gen victimr = (7-victim)/6

. 
. label var outgroupr "Outgroup"

. label var ingroupr "Ingroup"

. label var victimr "Victim"

. 
. 
. 
. save "Study2_clean.dta", replace
file Study2_clean.dta saved

. 
. 
end of do-file

. 
. *** Produce the data to compile the human trafficking figure in R.
. do "Human_Trafficking_Figure.do"

. /// This file creates the raw data outputs for Figure 1. The graphs are created 
> /// by the file Figures.R. It also contains calculations for Beta values 
> /// mentioned in the text.
> 
. 
. use "Study1_clean.dta", clear

. 
. 
. 
. *** Generate data for Figure 1 (Human Trafficking Attitudes for Republicans, Study 1) 
. 
. set more off

. mat results = J(2,4,0)

. local a=1

. local b=1

. foreach var of varlist problemR concernR{
  2. reg `var' treat if rep == 1, robust
  3.         mat results[`a',1] = _b[treat]
  4.         mat results[`a',2] = _se[treat]
  5.         mat results[`a',3] = `a'
  6.         mat results[`a',3] = 1
  7.         mat results[`a',4] = `b'
  8.         local ++a
  9.         local ++b
 10.         }

Linear regression                               Number of obs     =        251
                                                F(1, 249)         =       0.34
                                                Prob > F          =     0.5619
                                                R-squared         =     0.0014
                                                Root MSE          =     .25916

------------------------------------------------------------------------------
             |               Robust
    problemR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |   .0190453   .0327891     0.58   0.562    -.0455341    .0836247
       _cons |   .6425926   .0223949    28.69   0.000      .598485    .6867002
------------------------------------------------------------------------------

Linear regression                               Number of obs     =        251
                                                F(1, 249)         =       0.39
                                                Prob > F          =     0.5347
                                                R-squared         =     0.0015
                                                Root MSE          =       .244

------------------------------------------------------------------------------
             |               Robust
    concernR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |   .0191571   .0308166     0.62   0.535    -.0415373    .0798514
       _cons |   .7222222   .0213074    33.90   0.000     .6802565     .764188
------------------------------------------------------------------------------

. mat2txt, matrix(results) saving(fig1a) replace 

. 
. *** Generate data for Figure 1 (Human Trafficking Attitudes for Democrats, Study 1)
. 
. set more off

. mat results = J(2,4,0)

. local a=1

. local b=1

. foreach var of varlist problemR concernR{
  2. reg `var' treat if rep == 0, robust
  3.         mat results[`a',1] = _b[treat]
  4.         mat results[`a',2] = _se[treat]
  5.         mat results[`a',3] = `a'
  6.         mat results[`a',3] = 1
  7.         mat results[`a',4] = `b'
  8.         local ++a
  9.         local ++b
 10.         }

Linear regression                               Number of obs     =        263
                                                F(1, 261)         =       0.07
                                                Prob > F          =     0.7935
                                                R-squared         =     0.0003
                                                Root MSE          =     .23527

------------------------------------------------------------------------------
             |               Robust
    problemR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |  -.0075979    .029002    -0.26   0.794    -.0647055    .0495097
       _cons |   .6982759   .0200192    34.88   0.000     .6588562    .7376955
------------------------------------------------------------------------------

Linear regression                               Number of obs     =        263
                                                F(1, 261)         =       0.53
                                                Prob > F          =     0.4672
                                                R-squared         =     0.0020
                                                Root MSE          =     .20675

------------------------------------------------------------------------------
             |               Robust
    concernR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |  -.0184687   .0253652    -0.73   0.467    -.0684151    .0314777
       _cons |   .7896552   .0179322    44.04   0.000     .7543449    .8249654
------------------------------------------------------------------------------

. mat2txt, matrix(results) saving(fig2a) replace 

. 
. 
. **** Study 1 Concern for Human Trafficking (mentioned in text) 
. ttest concernR if rep == 0, by(treat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]
---------+--------------------------------------------------------------------
       0 |     145    .7896552    .0179258    .2158556    .7542234    .8250869
       1 |     118    .7711864    .0179474    .1949586    .7356426    .8067303
---------+--------------------------------------------------------------------
combined |     263    .7813688     .012737    .2065595    .7562889    .8064487
---------+--------------------------------------------------------------------
    diff |            .0184687    .0256329               -.0320048    .0689422
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =   0.7205
Ho: diff = 0                                     degrees of freedom =      261

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.7641         Pr(|T| > |t|) = 0.4719          Pr(T > t) = 0.2359

. ttest concernR if rep == 1, by(treat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]
---------+--------------------------------------------------------------------
       0 |     135    .7222222    .0213014    .2474999    .6800918    .7643527
       1 |     116    .7413793    .0222706    .2398619    .6972655    .7854931
---------+--------------------------------------------------------------------
combined |     251    .7310757    .0153823    .2437015    .7007803    .7613711
---------+--------------------------------------------------------------------
    diff |           -.0191571    .0308912               -.0799984    .0416842
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -0.6201
Ho: diff = 0                                     degrees of freedom =      249

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.2679         Pr(|T| > |t|) = 0.5357          Pr(T > t) = 0.7321

. ttest concernR if treat !=., by(rep)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]
---------+--------------------------------------------------------------------
       0 |     263    .7813688     .012737    .2065595    .7562889    .8064487
       1 |     251    .7310757    .0153823    .2437015    .7007803    .7613711
---------+--------------------------------------------------------------------
combined |     514    .7568093    .0099968    .2266424    .7371697     .776449
---------+--------------------------------------------------------------------
    diff |            .0502931    .0198947                .0112078    .0893785
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =   2.5280
Ho: diff = 0                                     degrees of freedom =      512

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.9941         Pr(|T| > |t|) = 0.0118          Pr(T > t) = 0.0059

. 
. 
. 
. *** Study 1 Scope of Trafficking Problem (mentioned in the text):
. use "Study1_clean.dta", clear

. 
. ttest problemR if rep == 0, by(treat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]
---------+--------------------------------------------------------------------
       0 |     145    .6982759    .0200121     .240977    .6587205    .7378312
       1 |     118     .690678    .0209936    .2280491    .6491012    .7322547
---------+--------------------------------------------------------------------
combined |     263    .6948669    .0144815    .2348507     .666352    .7233819
---------+--------------------------------------------------------------------
    diff |            .0075979    .0291688               -.0498382     .065034
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =   0.2605
Ho: diff = 0                                     degrees of freedom =      261

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.6027         Pr(|T| > |t|) = 0.7947          Pr(T > t) = 0.3973

. ttest problemR if rep == 1, by(treat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]
---------+--------------------------------------------------------------------
       0 |     135    .6425926    .0223886    .2601319    .5983119    .6868733
       1 |     116    .6616379    .0239577    .2580325    .6141823    .7090936
---------+--------------------------------------------------------------------
combined |     251    .6513944    .0163366    .2588205    .6192195    .6835693
---------+--------------------------------------------------------------------
    diff |           -.0190453    .0328108               -.0836673    .0455767
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -0.5805
Ho: diff = 0                                     degrees of freedom =      249

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.2811         Pr(|T| > |t|) = 0.5621          Pr(T > t) = 0.7189

. ttest problemR if treat !=., by(rep)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]
---------+--------------------------------------------------------------------
       0 |     263    .6948669    .0144815    .2348507     .666352    .7233819
       1 |     251    .6513944    .0163366    .2588205    .6192195    .6835693
---------+--------------------------------------------------------------------
combined |     514    .6736381    .0109195    .2475624    .6521857    .6950906
---------+--------------------------------------------------------------------
    diff |            .0434725    .0217817                .0006799    .0862651
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =   1.9958
Ho: diff = 0                                     degrees of freedom =      512

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.9768         Pr(|T| > |t|) = 0.0465          Pr(T > t) = 0.0232

. 
. 
. 
. *** Generate data for Figure 1 (Human Trafficking Attitudes for Republicans, Study 2) 
. 
. use "Study2_clean.dta", clear

. 
. set more off

. mat results = J(6,4,0)

. local a=1

. local b=1

. foreach var of varlist problemR concernR{
  2. reg `var' treat22 treat23 treat24 trump if rep == 1, robust
  3.         mat results[`a',1] = _b[treat22]
  4.         mat results[`a',2] = _se[treat22]
  5.         mat results[`a',3] = `a'
  6.         mat results[`a',3] = 1
  7.         mat results[`a',4] = `b'
  8.         local ++a
  9.         mat results[`a',1] = _b[treat23]
 10.         mat results[`a',2] = _se[treat23]
 11.         mat results[`a',3] = `a'
 12.         mat results[`a',3] = 2
 13.         mat results[`a',4] = `b'
 14.         local ++a
 15.         mat results[`a',1] = _b[treat24]
 16.         mat results[`a',2] = _se[treat24]
 17.         mat results[`a',3] = `a'
 18.         mat results[`a',3] = 3
 19.         mat results[`a',4] = `b'
 20.         local ++a
 21.         local ++b
 22.         }

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =       1.06
                                                Prob > F          =     0.3758
                                                R-squared         =     0.0095
                                                Root MSE          =     .26409

------------------------------------------------------------------------------
             |               Robust
    problemR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0145303   .0349275     0.42   0.678    -.0541131    .0831737
     treat23 |  -.0019212   .0344969    -0.06   0.956    -.0697183    .0658759
     treat24 |  -.0387414   .0353759    -1.10   0.274     -.108266    .0307832
       trump |   .0364006   .0288284     1.26   0.207    -.0202562    .0930574
       _cons |   .6478848   .0329447    19.67   0.000     .5831382    .7126313
------------------------------------------------------------------------------

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =       0.58
                                                Prob > F          =     0.6745
                                                R-squared         =     0.0051
                                                Root MSE          =     .26127

------------------------------------------------------------------------------
             |               Robust
    concernR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0156442    .035507     0.44   0.660     -.054138    .0854264
     treat23 |  -.0268555   .0340138    -0.79   0.430    -.0937032    .0399922
     treat24 |  -.0284909   .0346505    -0.82   0.411    -.0965898     .039608
       trump |  -.0141781   .0273763    -0.52   0.605    -.0679809    .0396248
       _cons |   .7384993   .0307189    24.04   0.000     .6781272    .7988714
------------------------------------------------------------------------------

. mat2txt, matrix(results) saving(fig1) replace 

. 
. 
. *** Generate data for Figure 1 (Human Trafficking Attitudes for Democrats, Study 2) 
. 
. set more off

. mat results = J(6,4,0)

. local a=1

. local b=1

. foreach var of varlist problemR concernR{
  2. reg `var' treat22 treat23 treat24 trump if rep == 0, robust
  3.         mat results[`a',1] = _b[treat22]
  4.         mat results[`a',2] = _se[treat22]
  5.         mat results[`a',3] = `a'
  6.         mat results[`a',3] = 1
  7.         mat results[`a',4] = `b'
  8.         local ++a
  9.         mat results[`a',1] = _b[treat23]
 10.         mat results[`a',2] = _se[treat23]
 11.         mat results[`a',3] = `a'
 12.         mat results[`a',3] = 2
 13.         mat results[`a',4] = `b'
 14.         local ++a
 15.         mat results[`a',1] = _b[treat24]
 16.         mat results[`a',2] = _se[treat24]
 17.         mat results[`a',3] = `a'
 18.         mat results[`a',3] = 3
 19.         mat results[`a',4] = `b'
 20.         local ++a
 21.         local ++b
 22.         }

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =       4.37
                                                Prob > F          =     0.0018
                                                R-squared         =     0.0371
                                                Root MSE          =     .23545

------------------------------------------------------------------------------
             |               Robust
    problemR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0519842   .0308216     1.69   0.092    -.0085854    .1125538
     treat23 |   .0016797   .0318211     0.05   0.958    -.0608542    .0642136
     treat24 |  -.0693691   .0335689    -2.07   0.039    -.1353375   -.0034006
       trump |  -.0585434   .0746397    -0.78   0.433    -.2052231    .0881363
       _cons |   .6856192   .0239058    28.68   0.000     .6386403     .732598
------------------------------------------------------------------------------

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =       4.00
                                                Prob > F          =     0.0033
                                                R-squared         =     0.0301
                                                Root MSE          =     .24877

------------------------------------------------------------------------------
             |               Robust
    concernR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0724773   .0317766     2.28   0.023      .010031    .1349236
     treat23 |   .0022512   .0346893     0.06   0.948     -.065919    .0704215
     treat24 |  -.0407132   .0339067    -1.20   0.230    -.1073456    .0259192
       trump |  -.0555263   .0677807    -0.82   0.413    -.1887269    .0776742
       _cons |   .7209111   .0244589    29.47   0.000     .6728452    .7689771
------------------------------------------------------------------------------

. mat2txt, matrix(results) saving(fig2) replace 

. 
. 
end of do-file

. 
. *** Produce the data to compile the immigration attitudes and mediation figures in R. 
. do "Immigration_Figure.do"

. /// This file creates the raw data outputs for Figure 2. The graphs are created 
> /// by the file Figures.R. It also contains calculations for Beta values
> /// mentioned in the text.
> 
. use "Study1_clean.dta", clear

. 
. *** Generate data for Figure 2 (Immigration Attitudes for Republicans, Study 1) 
. 
. set more off

. mat results = J(1,4,0)

. local a=1

. local b=1

. foreach var of varlist r_immR{
  2. reg `var' treat if rep == 1, robust
  3.         mat results[`a',1] = _b[treat]
  4.         mat results[`a',2] = _se[treat]
  5.         mat results[`a',3] = `a'
  6.         mat results[`a',3] = 1
  7.         mat results[`a',4] = `b'
  8.         local ++a
  9.         local ++b
 10.         }

Linear regression                               Number of obs     =        251
                                                F(1, 249)         =       8.22
                                                Prob > F          =     0.0045
                                                R-squared         =     0.0315
                                                Root MSE          =     .30312

------------------------------------------------------------------------------
             |               Robust
      r_immR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |   .1091794   .0380852     2.87   0.005     .0341692    .1841897
       _cons |   .2981481   .0272618    10.94   0.000     .2444549    .3518413
------------------------------------------------------------------------------

. mat2txt, matrix(results) saving(fig3a) replace 

. 
. *** Generate data for Figure 2 (Immigration Attitudes for Democrats, Study 1) 
. 
. set more off

. mat results = J(1,4,0)

. local a=1

. local b=1

. foreach var of varlist r_immR{
  2. reg `var' treat if rep == 0, robust
  3.         mat results[`a',1] = _b[treat]
  4.         mat results[`a',2] = _se[treat]
  5.         mat results[`a',3] = `a'
  6.         mat results[`a',3] = 1
  7.         mat results[`a',4] = `b'
  8.         local ++a
  9.         local ++b
 10.         }

Linear regression                               Number of obs     =        263
                                                F(1, 261)         =       0.03
                                                Prob > F          =     0.8719
                                                R-squared         =     0.0001
                                                Root MSE          =     .27234

------------------------------------------------------------------------------
             |               Robust
      r_immR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |   .0054208   .0335791     0.16   0.872    -.0606997    .0715413
       _cons |   .5051724   .0231516    21.82   0.000     .4595847    .5507601
------------------------------------------------------------------------------

. mat2txt, matrix(results) saving(fig4a) replace 

. 
. 
. *** Study 1 Immigration Attitudes (mentioned in the text): 
. 
. use "Study1_clean.dta", clear

. 
. ttest r_immR if rep == 0, by(treat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]
---------+--------------------------------------------------------------------
       0 |     145    .5051724    .0231433    .2786827    .4594279     .550917
       1 |     118    .5105932    .0243327    .2643207    .4624036    .5587829
---------+--------------------------------------------------------------------
combined |     263    .5076046    .0167618    .2718314    .4745995    .5406096
---------+--------------------------------------------------------------------
    diff |           -.0054208    .0337646               -.0719065    .0610649
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -0.1605
Ho: diff = 0                                     degrees of freedom =      261

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.4363         Pr(|T| > |t|) = 0.8726          Pr(T > t) = 0.5637

. ttest r_immR if rep == 1, by(treat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]
---------+--------------------------------------------------------------------
       0 |     135    .2981481    .0272541    .3166645    .2442442    .3520521
       1 |     116    .4073276    .0266034    .2865275    .3546313    .4600238
---------+--------------------------------------------------------------------
combined |     251    .3486056    .0194022    .3073891    .3103929    .3868182
---------+--------------------------------------------------------------------
    diff |           -.1091794    .0383754               -.1847613   -.0335976
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -2.8450
Ho: diff = 0                                     degrees of freedom =      249

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0024         Pr(|T| > |t|) = 0.0048          Pr(T > t) = 0.9976

. ttest r_immR if treat !=., by(rep)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]
---------+--------------------------------------------------------------------
       0 |     263    .5076046    .0167618    .2718314    .4745995    .5406096
       1 |     251    .3486056    .0194022    .3073891    .3103929    .3868182
---------+--------------------------------------------------------------------
combined |     514    .4299611    .0132408    .3001903    .4039482     .455974
---------+--------------------------------------------------------------------
    diff |             .158999    .0255667                .1087705    .2092275
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =   6.2190
Ho: diff = 0                                     degrees of freedom =      512

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 1.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 0.0000

. 
. 
. 
. *** Generate Data for Figure 2 (Immigration Attutidues for Republicans, Study 2)
. 
. use "Study2_clean.dta", clear

. 
. 
. set more off

. mat results = J(18,4,0)

. local a=1

. local b=1

. foreach var of varlist immR wallR2 uacR hawkeyeR legalR immig_index{
  2. reg `var' treat22 treat23 treat24 trump if rep == 1, robust
  3.         mat results[`a',1] = _b[treat22]
  4.         mat results[`a',2] = _se[treat22]
  5.         mat results[`a',3] = `a'
  6.         mat results[`a',3] = 1
  7.         mat results[`a',4] = `b'
  8.         local ++a
  9.         mat results[`a',1] = _b[treat23]
 10.         mat results[`a',2] = _se[treat23]
 11.         mat results[`a',3] = `a'
 12.         mat results[`a',3] = 2
 13.         mat results[`a',4] = `b'
 14.         local ++a
 15.         mat results[`a',1] = _b[treat24]
 16.         mat results[`a',2] = _se[treat24]
 17.         mat results[`a',3] = `a'
 18.         mat results[`a',3] = 3
 19.         mat results[`a',4] = `b'
 20.         local ++a
 21.         local ++b
 22.         }

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =      11.95
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0991
                                                Root MSE          =      .2451

------------------------------------------------------------------------------
             |               Robust
        immR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0819087   .0317964     2.58   0.010      .019419    .1443985
     treat23 |   .0887724   .0322068     2.76   0.006     .0254761    .1520686
     treat24 |   .0353617   .0306709     1.15   0.250    -.0249161    .0956395
       trump |  -.1584014   .0276759    -5.72   0.000     -.212793   -.1040098
       _cons |    .346706   .0302519    11.46   0.000     .2872517    .4061603
------------------------------------------------------------------------------

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =      29.87
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2625
                                                Root MSE          =     .25491

------------------------------------------------------------------------------
             |               Robust
      wallR2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0873625    .036843     2.37   0.018     .0149546    .1597704
     treat23 |   .0248959   .0329221     0.76   0.450    -.0398062     .089598
     treat24 |    .018289   .0320011     0.57   0.568     -.044603    .0811811
       trump |  -.3395809   .0327449   -10.37   0.000    -.4039348   -.2752269
       _cons |   .4775425   .0381878    12.51   0.000     .4024917    .5525933
------------------------------------------------------------------------------

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =       9.15
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0818
                                                Root MSE          =     .45423

------------------------------------------------------------------------------
             |               Robust
        uacR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0998992    .060364     1.65   0.099    -.0187346    .2185331
     treat23 |   .0200342   .0601947     0.33   0.739    -.0982671    .1383354
     treat24 |   .0251181   .0577516     0.43   0.664    -.0883816    .1386178
       trump |  -.3000984    .052096    -5.76   0.000    -.4024831   -.1977136
       _cons |   .5205684   .0588394     8.85   0.000     .4049308     .636206
------------------------------------------------------------------------------

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =       5.71
                                                Prob > F          =     0.0002
                                                R-squared         =     0.0478
                                                Root MSE          =     .31255

------------------------------------------------------------------------------
             |               Robust
    hawkeyeR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0418414   .0422284     0.99   0.322    -.0411506    .1248333
     treat23 |   .0170615   .0412679     0.41   0.679    -.0640427    .0981657
     treat24 |    .017641   .0406859     0.43   0.665    -.0623193    .0976013
       trump |  -.1557537   .0336533    -4.63   0.000    -.2218929   -.0896146
       _cons |   .4655459    .038891    11.97   0.000     .3891131    .5419788
------------------------------------------------------------------------------

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =       8.04
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0713
                                                Root MSE          =     .30779

------------------------------------------------------------------------------
             |               Robust
      legalR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0506305   .0406487     1.25   0.214    -.0292568    .1305179
     treat23 |  -.0081715   .0416219    -0.20   0.844    -.0899714    .0736285
     treat24 |  -.0266784   .0408368    -0.65   0.514    -.1069354    .0535785
       trump |  -.1873605   .0349775    -5.36   0.000    -.2561022   -.1186189
       _cons |   .5857862   .0416426    14.07   0.000     .5039457    .6676268
------------------------------------------------------------------------------

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =      20.78
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1739
                                                Root MSE          =     .22588

------------------------------------------------------------------------------
             |               Robust
 immig_index |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0723285   .0294754     2.45   0.015     .0144003    .1302566
     treat23 |   .0285185   .0303451     0.94   0.348    -.0311189    .0881559
     treat24 |   .0139463   .0296187     0.47   0.638    -.0442637    .0721563
       trump |   -.228239   .0269447    -8.47   0.000    -.2811936   -.1752844
       _cons |   .4792298   .0313787    15.27   0.000     .4175609    .5408987
------------------------------------------------------------------------------

. mat2txt, matrix(results) saving(fig3) replace 

. 
. 
. *** Generate Data for Figure 2 (Immigration Attutidues for Democrats, Study 2)
. 
. set more off

. mat results = J(18,4,0)

. local a=1

. local b=1

. foreach var of varlist immR wallR2 uacR hawkeyeR legalR immig_index{
  2. reg `var' treat22 treat23 treat24 trump if rep == 0, robust
  3.         mat results[`a',1] = _b[treat22]
  4.         mat results[`a',2] = _se[treat22]
  5.         mat results[`a',3] = `a'
  6.         mat results[`a',3] = 1
  7.         mat results[`a',4] = `b'
  8.         local ++a
  9.         mat results[`a',1] = _b[treat23]
 10.         mat results[`a',2] = _se[treat23]
 11.         mat results[`a',3] = `a'
 12.         mat results[`a',3] = 2
 13.         mat results[`a',4] = `b'
 14.         local ++a
 15.         mat results[`a',1] = _b[treat24]
 16.         mat results[`a',2] = _se[treat24]
 17.         mat results[`a',3] = `a'
 18.         mat results[`a',3] = 3
 19.         mat results[`a',4] = `b'
 20.         local ++a
 21.         local ++b
 22.         }

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =       9.43
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0749
                                                Root MSE          =     .24208

------------------------------------------------------------------------------
             |               Robust
        immR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |    .083348   .0319513     2.61   0.009     .0205582    .1461378
     treat23 |   .1196946   .0328269     3.65   0.000     .0551843     .184205
     treat24 |   .0227566   .0321934     0.71   0.480    -.0405089    .0860221
       trump |  -.2788666   .0674622    -4.13   0.000    -.4114413    -.146292
       _cons |   .5385528   .0235332    22.88   0.000     .4923062    .5847995
------------------------------------------------------------------------------

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =      27.08
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1412
                                                Root MSE          =     .24154

------------------------------------------------------------------------------
             |               Robust
      wallR2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0097492   .0321757    -0.30   0.762    -.0729799    .0534814
     treat23 |   .0474778    .031667     1.50   0.134    -.0147531    .1097087
     treat24 |   .0037485   .0334914     0.11   0.911    -.0620678    .0695648
       trump |  -.5455749   .0528673   -10.32   0.000    -.6494681   -.4416818
       _cons |   .8361955   .0236238    35.40   0.000     .7897707    .8826203
------------------------------------------------------------------------------

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =       4.87
                                                Prob > F          =     0.0007
                                                R-squared         =     0.0498
                                                Root MSE          =     .41346

------------------------------------------------------------------------------
             |               Robust
        uacR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0344319   .0574709     0.60   0.549    -.0785081    .1473719
     treat23 |   .0556361   .0569089     0.98   0.329    -.0561995    .1674717
     treat24 |   .0454337   .0574862     0.79   0.430    -.0675364    .1584038
       trump |  -.5244533   .1200777    -4.37   0.000    -.7604262   -.2884805
       _cons |   .7506921   .0435132    17.25   0.000     .6651813    .8362029
------------------------------------------------------------------------------

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =       1.87
                                                Prob > F          =     0.1143
                                                R-squared         =     0.0234
                                                Root MSE          =     .22899

------------------------------------------------------------------------------
             |               Robust
    hawkeyeR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0032665   .0298322    -0.11   0.913    -.0618917    .0553587
     treat23 |   .0368273   .0317036     1.16   0.246    -.0254757    .0991303
     treat24 |   .0057132   .0311226     0.18   0.854    -.0554479    .0668743
       trump |  -.1842863   .0782619    -2.35   0.019    -.3380841   -.0304886
       _cons |   .6561591   .0227071    28.90   0.000     .6115358    .7007823
------------------------------------------------------------------------------

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =       6.07
                                                Prob > F          =     0.0001
                                                R-squared         =     0.0699
                                                Root MSE          =     .24012

------------------------------------------------------------------------------
             |               Robust
      legalR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0089983   .0303747     0.30   0.767    -.0506931    .0686897
     treat23 |   .0338273   .0307313     1.10   0.272    -.0265649    .0942196
     treat24 |   .0294482   .0302982     0.97   0.332     -.030093    .0889893
       trump |  -.3680107   .0770171    -4.78   0.000    -.5193622   -.2166592
       _cons |    .787145   .0202623    38.85   0.000     .7473262    .8269637
------------------------------------------------------------------------------

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =      12.76
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1110
                                                Root MSE          =     .19791

------------------------------------------------------------------------------
             |               Robust
 immig_index |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0227525   .0249204     0.91   0.362    -.0262204    .0717253
     treat23 |   .0586926   .0265983     2.21   0.028     .0064224    .1109628
     treat24 |     .02142   .0267235     0.80   0.423    -.0310961    .0739362
       trump |  -.3802384   .0557099    -6.83   0.000    -.4897177   -.2707591
       _cons |   .7137489    .018472    38.64   0.000     .6774482    .7500495
------------------------------------------------------------------------------

. mat2txt, matrix(results) saving(fig4) replace

. 
. 
. *** Calculate Cronbach's Alpha for Immigration Index (mentioned in text) 
. 
. alpha immR wallR2 uacR legalR hawkeyeR 

Test scale = mean(unstandardized items)

Average interitem covariance:     .0774454
Number of items in the scale:            5
Scale reliability coefficient:      0.8600

. /*
> Average interitem covariance:     .0774454
> Number of items in the scale:            5
> Scale reliability coefficient:      0.8600
> */
. factor immR wallR2 uacR legalR hawkeyeR 
(obs=987)

Factor analysis/correlation                      Number of obs    =        987
    Method: principal factors                    Retained factors =          2
    Rotation: (unrotated)                        Number of params =          9

    --------------------------------------------------------------------------
         Factor  |   Eigenvalue   Difference        Proportion   Cumulative
    -------------+------------------------------------------------------------
        Factor1  |      2.89335      2.78729            1.0854       1.0854
        Factor2  |      0.10606      0.16934            0.0398       1.1251
        Factor3  |     -0.06328      0.06668           -0.0237       1.1014
        Factor4  |     -0.12996      0.01038           -0.0488       1.0526
        Factor5  |     -0.14034            .           -0.0526       1.0000
    --------------------------------------------------------------------------
    LR test: independent vs. saturated:  chi2(10) = 2492.33 Prob>chi2 = 0.0000

Factor loadings (pattern matrix) and unique variances

    -------------------------------------------------
        Variable |  Factor1   Factor2 |   Uniqueness 
    -------------+--------------------+--------------
            immR |   0.7360    0.1331 |      0.4406  
          wallR2 |   0.7727    0.1418 |      0.3829  
            uacR |   0.6663    0.1000 |      0.5460  
          legalR |   0.8309   -0.1534 |      0.2862  
        hawkeyeR |   0.7876   -0.1863 |      0.3449  
    -------------------------------------------------

. rotate

Factor analysis/correlation                      Number of obs    =        987
    Method: principal factors                    Retained factors =          2
    Rotation: orthogonal varimax (Kaiser off)    Number of params =          9

    --------------------------------------------------------------------------
         Factor  |     Variance   Difference        Proportion   Cumulative
    -------------+------------------------------------------------------------
        Factor1  |      1.81238      0.62536            0.6799       0.6799
        Factor2  |      1.18702            .            0.4453       1.1251
    --------------------------------------------------------------------------
    LR test: independent vs. saturated:  chi2(10) = 2492.33 Prob>chi2 = 0.0000

Rotated factor loadings (pattern matrix) and unique variances

    -------------------------------------------------
        Variable |  Factor1   Factor2 |   Uniqueness 
    -------------+--------------------+--------------
            immR |   0.4930    0.5625 |      0.4406  
          wallR2 |   0.5162    0.5922 |      0.3829  
            uacR |   0.4591    0.4932 |      0.5460  
          legalR |   0.7456    0.3974 |      0.2862  
        hawkeyeR |   0.7323    0.3447 |      0.3449  
    -------------------------------------------------

Factor rotation matrix

    --------------------------------
                 | Factor1  Factor2 
    -------------+------------------
         Factor1 |  0.7824   0.6228 
         Factor2 | -0.6228   0.7824 
    --------------------------------

. 
. 
. 
. *** Generating Data for Figure 3 (Explanations of Immigration Attitudes for Republicans, Study 2) 
. 
. set more off

. mat results = J(15,4,0)

. local a=1

. local b=1

. foreach var of varlist econ_threa2 cultl_thre2 outgroupr ingroupr victimr{
  2. reg `var' treat22 treat23 treat24 trump if rep == 1, robust
  3.         mat results[`a',1] = _b[treat22]
  4.         mat results[`a',2] = _se[treat22]
  5.         mat results[`a',3] = `a'
  6.         mat results[`a',3] = 1
  7.         mat results[`a',4] = `b'
  8.         local ++a
  9.         mat results[`a',1] = _b[treat23]
 10.         mat results[`a',2] = _se[treat23]
 11.         mat results[`a',3] = `a'
 12.         mat results[`a',3] = 2
 13.         mat results[`a',4] = `b'
 14.         local ++a
 15.         mat results[`a',1] = _b[treat24]
 16.         mat results[`a',2] = _se[treat24]
 17.         mat results[`a',3] = `a'
 18.         mat results[`a',3] = 3
 19.         mat results[`a',4] = `b'
 20.         local ++a
 21.         local ++b
 22.         }

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =       8.52
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0733
                                                Root MSE          =     .23582

------------------------------------------------------------------------------
             |               Robust
 econ_threa2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0724354   .0312333    -2.32   0.021    -.1338185   -.0110522
     treat23 |  -.0668986   .0299517    -2.23   0.026     -.125763   -.0080341
     treat24 |  -.0170711   .0299205    -0.57   0.569    -.0758741    .0417318
       trump |   .1287081   .0266099     4.84   0.000     .0764113    .1810048
       _cons |   .6839295    .028962    23.61   0.000     .6270102    .7408488
------------------------------------------------------------------------------

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =       6.70
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0557
                                                Root MSE          =       .279

------------------------------------------------------------------------------
             |               Robust
cultl_t~2_v2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0214311   .0387438    -0.55   0.580    -.0975747    .0547125
     treat23 |  -.0148694   .0354442    -0.42   0.675    -.0845282    .0547895
     treat24 |    .041224   .0381295     1.08   0.280    -.0337121    .1161602
       trump |   .1426296   .0316286     4.51   0.000     .0804696    .2047897
       _cons |   .4954933   .0373704    13.26   0.000     .4220488    .5689378
------------------------------------------------------------------------------

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =      10.29
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0864
                                                Root MSE          =     .26111

------------------------------------------------------------------------------
             |               Robust
   outgroupr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   -.101265    .035754    -2.83   0.005    -.1715326   -.0309973
     treat23 |  -.0384428   .0348311    -1.10   0.270    -.1068967     .030011
     treat24 |  -.0604278   .0345437    -1.75   0.081    -.1283169    .0074613
       trump |   .1642096   .0280496     5.85   0.000     .1090834    .2193359
       _cons |   .3297821   .0323224    10.20   0.000     .2662586    .3933056
------------------------------------------------------------------------------

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =       8.29
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0640
                                                Root MSE          =     .31826

------------------------------------------------------------------------------
             |               Robust
    ingroupr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0863754   .0446556    -1.93   0.054    -.1741374    .0013866
     treat23 |  -.0632043   .0425479    -1.49   0.138    -.1468241    .0204155
     treat24 |  -.0174102    .042506    -0.41   0.682    -.1009477    .0661272
       trump |   .1692871   .0350926     4.82   0.000     .1003193    .2382548
       _cons |   .4774677   .0420311    11.36   0.000     .3948636    .5600719
------------------------------------------------------------------------------

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =       9.50
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0754
                                                Root MSE          =     .29769

------------------------------------------------------------------------------
             |               Robust
     victimr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.1093217   .0410641    -2.66   0.008    -.1900253    -.028618
     treat23 |  -.0294516   .0374875    -0.79   0.432     -.103126    .0442229
     treat24 |  -.0161874   .0396273    -0.41   0.683    -.0940673    .0616925
       trump |    .172735   .0330303     5.23   0.000     .1078203    .2376497
       _cons |   .5526517   .0387066    14.28   0.000     .4765814    .6287221
------------------------------------------------------------------------------

. mat2txt, matrix(results) saving(fig5) replace 

. 
. 
. *** Generating Data for Figure 3 (Explanations of Immigration Attitudes for Democrats, Study 2) 
. 
. set more off

. mat results = J(15,4,0)

. local a=1

. local b=1

. foreach var of varlist econ_threa2 cultl_thre2 outgroupr ingroupr victimr{
  2. reg `var' treat22 treat23 treat24 trump if rep == 0, robust
  3.         mat results[`a',1] = _b[treat22]
  4.         mat results[`a',2] = _se[treat22]
  5.         mat results[`a',3] = `a'
  6.         mat results[`a',3] = 1
  7.         mat results[`a',4] = `b'
  8.         local ++a
  9.         mat results[`a',1] = _b[treat23]
 10.         mat results[`a',2] = _se[treat23]
 11.         mat results[`a',3] = `a'
 12.         mat results[`a',3] = 2
 13.         mat results[`a',4] = `b'
 14.         local ++a
 15.         mat results[`a',1] = _b[treat24]
 16.         mat results[`a',2] = _se[treat24]
 17.         mat results[`a',3] = `a'
 18.         mat results[`a',3] = 3
 19.         mat results[`a',4] = `b'
 20.         local ++a
 21.         local ++b
 22.         }

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =      15.48
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0569
                                                Root MSE          =     .26269

------------------------------------------------------------------------------
             |               Robust
 econ_threa2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   -.011011   .0351133    -0.31   0.754    -.0800146    .0579927
     treat23 |  -.0212398   .0355276    -0.60   0.550    -.0910575    .0485779
     treat24 |  -.0010545   .0354996    -0.03   0.976    -.0708173    .0687082
       trump |   .3593393   .0469184     7.66   0.000     .2671367    .4515418
       _cons |   .3829118   .0260315    14.71   0.000     .3317555    .4340681
------------------------------------------------------------------------------

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =       3.42
                                                Prob > F          =     0.0091
                                                R-squared         =     0.0349
                                                Root MSE          =     .23299

------------------------------------------------------------------------------
             |               Robust
cultl_t~2_v2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0228293   .0301453     0.76   0.449    -.0364113    .0820698
     treat23 |  -.0193767   .0322508    -0.60   0.548    -.0827549    .0440015
     treat24 |   .0095885    .032604     0.29   0.769    -.0544838    .0736607
       trump |   .2400595   .0742825     3.23   0.001     .0940818    .3860372
       _cons |   .2416335   .0234397    10.31   0.000     .1955706    .2876964
------------------------------------------------------------------------------

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =       2.28
                                                Prob > F          =     0.0603
                                                R-squared         =     0.0186
                                                Root MSE          =     .20465

------------------------------------------------------------------------------
             |               Robust
   outgroupr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0348669   .0279134    -1.25   0.212    -.0897215    .0199877
     treat23 |  -.0593051   .0281266    -2.11   0.036    -.1145785   -.0040316
     treat24 |   -.026927   .0300019    -0.90   0.370    -.0858858    .0320319
       trump |    .109176   .0469209     2.33   0.020     .0169686    .2013834
       _cons |   .1808724    .022206     8.15   0.000     .1372339    .2245109
------------------------------------------------------------------------------

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =       3.79
                                                Prob > F          =     0.0048
                                                R-squared         =     0.0323
                                                Root MSE          =     .28235

------------------------------------------------------------------------------
             |               Robust
    ingroupr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0557264   .0387419    -1.44   0.151    -.1318607    .0204079
     treat23 |  -.0820027   .0391622    -2.09   0.037    -.1589631   -.0050423
     treat24 |   -.050335   .0397867    -1.27   0.206    -.1285224    .0278525
       trump |   .2435815     .07572     3.22   0.001     .0947789    .3923841
       _cons |   .2871313   .0302091     9.50   0.000     .2277653    .3464974
------------------------------------------------------------------------------

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =       9.36
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0724
                                                Root MSE          =     .27845

------------------------------------------------------------------------------
             |               Robust
     victimr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0542397   .0372951    -1.45   0.147    -.1275309    .0190516
     treat23 |  -.0896422   .0375822    -2.39   0.017    -.1634976   -.0157868
     treat24 |  -.0564396   .0386123    -1.46   0.145    -.1323193    .0194402
       trump |   .4063051   .0712837     5.70   0.000     .2662205    .5463896
       _cons |   .3076832   .0280765    10.96   0.000     .2525082    .3628582
------------------------------------------------------------------------------

. mat2txt, matrix(results) saving(fig6) replace 

. 
. 
. 
. 
end of do-file

. 
. *** Produce the tables found in the appendices.
. do "ManipulationChecks.do"

. 
. /// This file creates the  calculations for manipulation checks that are 
> /// mentioned in the text of the appendix.
> 
. 
. ***** Study 1 MANIPULATION CHECK (mentioned in text of appendix) 
. 
. use "Study1_clean.dta", clear

. 
. 
. * Immig - immigration treatment moves people on thinking immigration is the most pressing problem
. gen manip_lab = 1 if ht_man1 == 2
(1,711 missing values generated)

. replace manip_lab = 0 if ht_man1 !=2
(1,711 real changes made)

. 
. * immigration t-test 
. ttest manip_lab, by(treat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]
---------+--------------------------------------------------------------------
       0 |     344    .1453488    .0190306    .3529656    .1079174    .1827803
       1 |     309     .197411    .0226807    .3986908    .1527822    .2420398
---------+--------------------------------------------------------------------
combined |     653    .1699847    .0147104    .3759073    .1410992    .1988701
---------+--------------------------------------------------------------------
    diff |           -.0520622    .0294151                -.109822    .0056977
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -1.7699
Ho: diff = 0                                     degrees of freedom =      651

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0386         Pr(|T| > |t|) = 0.0772          Pr(T > t) = 0.9614

. 
. 
. ***** Study 2 MANIPULATION CHECK (mentioned in text of appendix)
. 
. use "Study2_clean.dta", clear

. 
. gen man_incR = (man_inc-1)/6

. 
. eststo  : reg man_incR treat22 treat23 treat24 trump, robust

Linear regression                               Number of obs     =        985
                                                F(4, 980)         =      36.60
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1333
                                                Root MSE          =     .28921

------------------------------------------------------------------------------
             |               Robust
    man_incR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .1130289   .0266619     4.24   0.000      .060708    .1653498
     treat23 |   .0902413   .0260022     3.47   0.001     .0392149    .1412678
     treat24 |  -.0038949   .0263012    -0.15   0.882    -.0555081    .0477182
       trump |  -.2015308   .0197264   -10.22   0.000    -.2402416   -.1628199
       _cons |   .5421157   .0203181    26.68   0.000     .5022437    .5819877
------------------------------------------------------------------------------
(est1 stored)

. eststo  : reg man_incR treat22 treat23 treat24 ageR female incomeR white rel trump college, robust

Linear regression                               Number of obs     =        985
                                                F(10, 974)        =      15.64
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1412
                                                Root MSE          =     .28877

------------------------------------------------------------------------------
             |               Robust
    man_incR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .1110133   .0266789     4.16   0.000     .0586586    .1633681
     treat23 |   .0907436   .0260114     3.49   0.001     .0396986    .1417885
     treat24 |  -.0059265   .0262506    -0.23   0.821    -.0574406    .0455877
        ageR |  -.1502437   .0692698    -2.17   0.030    -.2861789   -.0143086
      female |   -.034342   .0190414    -1.80   0.072    -.0717088    .0030249
     incomeR |   .0033808   .0450257     0.08   0.940    -.0849777    .0917393
       white |  -.0204581   .0241266    -0.85   0.397    -.0678043    .0268881
         rel |  -.0010987   .0061529    -0.18   0.858    -.0131733    .0109758
       trump |  -.1914557   .0217433    -8.81   0.000    -.2341248   -.1487866
     college |    .008468   .0193635     0.44   0.662     -.029531     .046467
       _cons |   .6062599   .0365981    16.57   0.000     .5344398    .6780801
------------------------------------------------------------------------------
(est2 stored)

. eststo  : reg man_incR treat22 treat23 treat24 trump if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =       4.83
                                                Prob > F          =     0.0008
                                                R-squared         =     0.0398
                                                Root MSE          =     .30495

------------------------------------------------------------------------------
             |               Robust
    man_incR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0847931   .0419103     2.02   0.044     .0024265    .1671598
     treat23 |   .0741489    .041011     1.81   0.071    -.0064503    .1547482
     treat24 |  -.0232977   .0393568    -0.59   0.554    -.1006461    .0540506
       trump |  -.0899627   .0319459    -2.82   0.005    -.1527463    -.027179
       _cons |   .4375392   .0376632    11.62   0.000     .3635195     .511559
------------------------------------------------------------------------------
(est3 stored)

. eststo  : reg man_incR treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(10, 439)        =       3.02
                                                Prob > F          =     0.0010
                                                R-squared         =     0.0620
                                                Root MSE          =     .30345

------------------------------------------------------------------------------
             |               Robust
    man_incR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |    .074796   .0418725     1.79   0.075    -.0074995    .1570915
     treat23 |   .0715806    .041126     1.74   0.082    -.0092478    .1524091
     treat24 |  -.0265813   .0387853    -0.69   0.493    -.1028093    .0496467
        ageR |  -.1984403   .0996393    -1.99   0.047    -.3942696    -.002611
      female |  -.0161126   .0303515    -0.53   0.596     -.075765    .0435398
     incomeR |    .063526   .0665979     0.95   0.341    -.0673644    .1944165
       white |  -.0806341   .0507094    -1.59   0.113    -.1802974    .0190292
         rel |   .0117059   .0084939     1.38   0.169    -.0049878    .0283996
       trump |  -.0931165   .0318688    -2.92   0.004    -.1557509   -.0304821
     college |   -.024874   .0307572    -0.81   0.419    -.0853237    .0355756
       _cons |   .5436911   .0729576     7.45   0.000     .4003016    .6870806
------------------------------------------------------------------------------
(est4 stored)

. eststo  : reg man_incR treat22 treat23 treat24 trump if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =       6.65
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0596
                                                Root MSE          =     .26363

------------------------------------------------------------------------------
             |               Robust
    man_incR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |    .109147   .0357286     3.05   0.002     .0389343    .1793598
     treat23 |   .1126601    .033467     3.37   0.001     .0468918    .1784284
     treat24 |  -.0068267   .0369424    -0.18   0.853    -.0794247    .0657713
       trump |  -.1719375    .086507    -1.99   0.047    -.3419384   -.0019366
       _cons |   .5740485   .0261578    21.95   0.000     .5226441     .625453
------------------------------------------------------------------------------
(est5 stored)

. eststo  : reg man_incR treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(10, 451)        =       3.21
                                                Prob > F          =     0.0005
                                                R-squared         =     0.0688
                                                Root MSE          =     .26407

------------------------------------------------------------------------------
             |               Robust
    man_incR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .1080336   .0363699     2.97   0.003     .0365581    .1795092
     treat23 |   .1117208   .0335134     3.33   0.001     .0458589    .1775827
     treat24 |  -.0113516   .0371488    -0.31   0.760    -.0843579    .0616547
        ageR |  -.0263021     .10402    -0.25   0.800    -.2307262    .1781221
      female |  -.0373039   .0253537    -1.47   0.142      -.08713    .0125221
     incomeR |  -.0231847   .0603659    -0.38   0.701     -.141818    .0954485
       white |   -.004846   .0293746    -0.16   0.869     -.062574     .052882
         rel |   .0045175   .0099863     0.45   0.651    -.0151079    .0241429
       trump |  -.1642968    .085923    -1.91   0.056     -.333156    .0045624
     college |   .0379806   .0256628     1.48   0.140    -.0124529    .0884141
       _cons |    .586052   .0462081    12.68   0.000     .4952421     .676862
------------------------------------------------------------------------------
(est6 stored)

. esttab using manipulation_check.tex, ar2 b(3) se(3) starlevels(* 0.1 ** .05 *** .01) label replace
(output written to manipulation_check.tex)

. eststo clear

. 
end of do-file

. do "Appendix_Study1.do"

. **** This file generates tables and notes found in the Appendices for Study 1.
. 
. use "Study1_clean.dta", clear

. 
. 
. **** Study Appendix Tables
. 
. *** Create Labels for Regression Tables
. label var treat "Treatment"

. label var pidnewR "Party Identification (Republican $\rightarrow$ Democrat)"

. label var ageR "Age"

. label var female "Female"

. label var incomeR "Income"

. label var white "White"

. label var religiosity "Religiosity"

. label var college "College Degree"

. label var rep "Republican"

. 
. label var concernR "Concern"

. label var problemR "Scope of Problem" 

. label var r_immR "Immigration Levels"

. 
. global control ageR female incomeR white religiosity college

. 
. 
. *** Table A.1 Study 1 Summary Statistics
. gen r_imm_R2 = (5-r_imm)
(14 missing values generated)

. 
. su concern problem r_imm_R2 age female white pidnew rep religiosity college if treat !=.

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
     concern |        653    4.015314    .9099374          1          5
     problem |        653    3.713629    .9918755          1          5
    r_imm_R2 |        650    1.732308    1.215857          0          4
         age |        653     48.2925     16.6915         18         86
      female |        653    .5053599    .5003545          0          1
-------------+---------------------------------------------------------
       white |        653    .7748851    .4179781          0          1
      pidnew |        645    3.074419    2.021018          0          6
         rep |        514    .4883268    .5003507          0          1
 religiosity |        653    .7519142    .4322329          0          1
     college |        653    .4808576    .5000164          0          1

. tab incomeR, gen(inc)

     Income |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |        108        5.56        5.56
   .0588235 |        158        8.14       13.70
   .1176471 |        207       10.66       24.36
   .1764706 |        247       12.72       37.08
   .2352941 |        188        9.68       46.76
   .3382353 |        403       20.75       67.51
   .4852941 |        285       14.68       82.18
   .7058824 |        236       12.15       94.34
          1 |        110        5.66      100.00
------------+-----------------------------------
      Total |      1,942      100.00

. su inc* if treat !=.

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
      income |        645    61.54651     43.9491          5        175
     incomeR |        645    .3326265    .2585241          0          1
        inc1 |        645    .0682171    .2523137          0          1
        inc2 |        645    .0899225    .2862927          0          1
        inc3 |        645    .0992248    .2991956          0          1
-------------+---------------------------------------------------------
        inc4 |        645    .1472868    .3546667          0          1
        inc5 |        645    .1023256    .3033112          0          1
        inc6 |        645    .1844961    .3881893          0          1
        inc7 |        645    .1364341    .3435153          0          1
        inc8 |        645    .1193798    .3244866          0          1
-------------+---------------------------------------------------------
        inc9 |        645    .0527132    .2236337          0          1

. 
. 
. *** Generate Table A.2 Study 1 Balance Tests
. 
. orth_out $control using balance1_dem.tex if rep == 0, by(treat) se pcompare test latex replace

                                0:            1:  (1) vs. (~e:  p-value f~y:
                                _             _             _             _
           Age:mean         0.447         0.391         0.064         0.171
                 se         0.020         0.023             .             .
        Female:mean         0.503         0.508         0.936         0.977
                 se         0.042         0.046             .             .
        Income:mean         0.338         0.292         0.144         0.134
                 se         0.023         0.021             .             .
         White:mean         0.703         0.653         0.380         0.432
                 se         0.038         0.044             .             .
   Religiosity:mean         0.703         0.720         0.765         0.889
                 se         0.038         0.041             .             .
College Degree:mean         0.517         0.508         0.888         0.989
                 se         0.042         0.046             .             .

. orth_out $control using balance_rep.tex if rep == 1, by(treat) se pcompare test latex replace

                                0:            1:  (1) vs. (~e:  p-value f~y:
                                _             _             _             _
           Age:mean         0.485         0.463         0.490         0.259
                 se         0.022         0.022             .             .
        Female:mean         0.452         0.569         0.065         0.162
                 se         0.043         0.046             .             .
        Income:mean         0.398         0.355         0.195         0.424
                 se         0.024         0.022             .             .
         White:mean         0.874         0.862         0.780         0.818
                 se         0.029         0.032             .             .
   Religiosity:mean         0.830         0.845         0.747         0.907
                 se         0.032         0.034             .             .
College Degree:mean         0.474         0.431         0.497         0.553
                 se         0.043         0.046             .             .

. 
. 
. ** Data for note on K-Smirnov Tests
. 
. ksmirnov r_imm, by(rep)

Two-sample Kolmogorov-Smirnov test for equality of distribution functions

 Smaller group       D       P-value  
 -----------------------------------
 0:                  0.2703    0.000
 1:                  0.0000    1.000
 Combined K-S:       0.2703    0.000

Note: Ties exist in combined dataset;
      there are 5 unique values out of 1516 observations.

. /*
> 
>  0:                  0.0000    1.000
>  1:                 -0.2703    0.000
>  Combined K-S:       0.2703    0.000
> 
>  P-Value < 0.000
> */
. ksmirnov concernR, by(rep)

Two-sample Kolmogorov-Smirnov test for equality of distribution functions

 Smaller group       D       P-value  
 -----------------------------------
 0:                  0.0000    1.000
 1:                 -0.0729    0.018
 Combined K-S:       0.0729    0.036

Note: Ties exist in combined dataset;
      there are 5 unique values out of 1516 observations.

. /*
>  0:                  0.0000    1.000
>  1:                 -0.0729    0.018
>  Combined K-S:       0.0729    0.036
> 
>  P-Value = 0.036
> */
. 
. 
. 
. 
. 
. *** Generate Table B.1 Concern For Trafficking
. 
. eststo: reg concernR treat if rep == 1, robust 

Linear regression                               Number of obs     =        251
                                                F(1, 249)         =       0.39
                                                Prob > F          =     0.5347
                                                R-squared         =     0.0015
                                                Root MSE          =       .244

------------------------------------------------------------------------------
             |               Robust
    concernR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |   .0191571   .0308166     0.62   0.535    -.0415373    .0798514
       _cons |   .7222222   .0213074    33.90   0.000     .6802565     .764188
------------------------------------------------------------------------------
(est1 stored)

. eststo: reg concernR treat $control if rep == 1, robust 

Linear regression                               Number of obs     =        251
                                                F(7, 243)         =       2.10
                                                Prob > F          =     0.0437
                                                R-squared         =     0.0530
                                                Root MSE          =     .24055

------------------------------------------------------------------------------
             |               Robust
    concernR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |   .0085066    .030388     0.28   0.780    -.0513509    .0683642
        ageR |  -.0014179   .0603712    -0.02   0.981    -.1203355    .1174997
      female |   .0853066   .0315105     2.71   0.007     .0232381    .1473751
     incomeR |   .0221738   .0660262     0.34   0.737     -.107883    .1522306
       white |  -.0233465   .0394279    -0.59   0.554    -.1010106    .0543175
 religiosity |   .0897897   .0447257     2.01   0.046     .0016901    .1778893
     college |   .0013807   .0333198     0.04   0.967    -.0642517    .0670131
       _cons |   .6208051   .0617777    10.05   0.000      .499117    .7424933
------------------------------------------------------------------------------
(est2 stored)

. eststo: reg concernR treat if rep == 0, robust 

Linear regression                               Number of obs     =        263
                                                F(1, 261)         =       0.53
                                                Prob > F          =     0.4672
                                                R-squared         =     0.0020
                                                Root MSE          =     .20675

------------------------------------------------------------------------------
             |               Robust
    concernR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |  -.0184687   .0253652    -0.73   0.467    -.0684151    .0314777
       _cons |   .7896552   .0179322    44.04   0.000     .7543449    .8249654
------------------------------------------------------------------------------
(est3 stored)

. eststo: reg concernR treat $control if rep == 0, robust 

Linear regression                               Number of obs     =        263
                                                F(7, 255)         =       2.51
                                                Prob > F          =     0.0165
                                                R-squared         =     0.0550
                                                Root MSE          =     .20354

------------------------------------------------------------------------------
             |               Robust
    concernR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |  -.0185552   .0250334    -0.74   0.459    -.0678538    .0307434
        ageR |  -.0216345   .0506491    -0.43   0.670    -.1213783    .0781093
      female |   .0531578   .0252723     2.10   0.036     .0033889    .1029268
     incomeR |   .0898123    .049237     1.82   0.069    -.0071506    .1867752
       white |  -.0417995    .027871    -1.50   0.135    -.0966862    .0130872
 religiosity |   .0117017   .0260262     0.45   0.653     -.039552    .0629555
     college |   -.047467   .0268661    -1.77   0.078    -.1003748    .0054408
       _cons |   .7879474   .0395661    19.91   0.000     .7100295    .8658653
------------------------------------------------------------------------------
(est4 stored)

. eststo: reg concernR treat rep treat_rep, robust 

Linear regression                               Number of obs     =        514
                                                F(3, 510)         =       2.32
                                                Prob > F          =     0.0744
                                                R-squared         =     0.0140
                                                Root MSE          =     .22571

------------------------------------------------------------------------------
             |               Robust
    concernR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |  -.0184687   .0253674    -0.73   0.467    -.0683062    .0313688
         rep |   -.067433   .0278486    -2.42   0.016     -.122145   -.0127209
   treat_rep |   .0376258   .0399123     0.94   0.346    -.0407869    .1160385
       _cons |   .7896552   .0179338    44.03   0.000     .7544219    .8248884
------------------------------------------------------------------------------
(est5 stored)

. eststo: reg concernR treat rep treat_rep $control, robust 

Linear regression                               Number of obs     =        514
                                                F(9, 504)         =       3.69
                                                Prob > F          =     0.0002
                                                R-squared         =     0.0551
                                                Root MSE          =     .22227

------------------------------------------------------------------------------
             |               Robust
    concernR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |  -.0199019   .0250826    -0.79   0.428    -.0691811    .0293774
         rep |  -.0662777   .0278685    -2.38   0.018    -.1210303    -.011525
   treat_rep |   .0307011   .0396011     0.78   0.439    -.0471024    .1085046
        ageR |   -.010879   .0391496    -0.28   0.781    -.0877955    .0660375
      female |   .0712114   .0198691     3.58   0.000     .0321749     .110248
     incomeR |   .0527155   .0403217     1.31   0.192    -.0265039    .1319348
       white |  -.0387618   .0226307    -1.71   0.087     -.083224    .0057003
 religiosity |   .0432196   .0235657     1.83   0.067    -.0030795    .0895187
     college |   -.021706   .0211268    -1.03   0.305    -.0632134    .0198013
       _cons |   .7489491    .033809    22.15   0.000     .6825251    .8153731
------------------------------------------------------------------------------
(est6 stored)

. esttab using output_concern_robust.tex, ar2(2) b(2) se(2) starlevels(* 0.1 ** .05 *** .01) label replace
(output written to output_concern_robust.tex)

. eststo clear

. 
. 
. ***Generate Table B.2 Scope of Trafficking
. 
. eststo: reg problemR treat if rep == 1, robust 

Linear regression                               Number of obs     =        251
                                                F(1, 249)         =       0.34
                                                Prob > F          =     0.5619
                                                R-squared         =     0.0014
                                                Root MSE          =     .25916

------------------------------------------------------------------------------
             |               Robust
    problemR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |   .0190453   .0327891     0.58   0.562    -.0455341    .0836247
       _cons |   .6425926   .0223949    28.69   0.000      .598485    .6867002
------------------------------------------------------------------------------
(est1 stored)

. eststo: reg problemR treat $control if rep == 1, robust 

Linear regression                               Number of obs     =        251
                                                F(7, 243)         =       0.79
                                                Prob > F          =     0.5975
                                                R-squared         =     0.0236
                                                Root MSE          =      .2594

------------------------------------------------------------------------------
             |               Robust
    problemR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |   .0126474   .0329675     0.38   0.702    -.0522911    .0775859
        ageR |  -.0658515   .0635762    -1.04   0.301    -.1910823    .0593794
      female |   .0231906   .0358683     0.65   0.519     -.047462    .0938431
     incomeR |  -.0378895   .0748758    -0.51   0.613    -.1853779    .1095988
       white |   .0862636   .0541598     1.59   0.113    -.0204189    .1929462
 religiosity |   .0644374   .0493506     1.31   0.193    -.0327722     .161647
     college |   -.015865   .0329097    -0.48   0.630    -.0806897    .0489597
       _cons |   .5577872   .0797086     7.00   0.000     .4007793    .7147952
------------------------------------------------------------------------------
(est2 stored)

. eststo: reg problemR treat if rep == 0, robust 

Linear regression                               Number of obs     =        263
                                                F(1, 261)         =       0.07
                                                Prob > F          =     0.7935
                                                R-squared         =     0.0003
                                                Root MSE          =     .23527

------------------------------------------------------------------------------
             |               Robust
    problemR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |  -.0075979    .029002    -0.26   0.794    -.0647055    .0495097
       _cons |   .6982759   .0200192    34.88   0.000     .6588562    .7376955
------------------------------------------------------------------------------
(est3 stored)

. eststo: reg problemR treat $control if rep == 0, robust 

Linear regression                               Number of obs     =        263
                                                F(7, 255)         =       2.02
                                                Prob > F          =     0.0529
                                                R-squared         =     0.0567
                                                Root MSE          =      .2312

------------------------------------------------------------------------------
             |               Robust
    problemR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |  -.0071683   .0285188    -0.25   0.802    -.0633306     .048994
        ageR |   .0017356   .0618152     0.03   0.978    -.1199976    .1234689
      female |    .092556   .0282919     3.27   0.001     .0368405    .1482714
     incomeR |   .0262164   .0562157     0.47   0.641    -.0844898    .1369226
       white |   .0000959   .0337593     0.00   0.998    -.0663866    .0665784
 religiosity |  -.0053725   .0289982    -0.19   0.853    -.0624789    .0517339
     college |  -.0581559   .0303624    -1.92   0.057    -.1179488    .0016371
       _cons |   .6758352   .0443842    15.23   0.000     .5884289    .7632415
------------------------------------------------------------------------------
(est4 stored)

. eststo: reg problemR treat rep treat_rep, robust 

Linear regression                               Number of obs     =        514
                                                F(3, 510)         =       1.44
                                                Prob > F          =     0.2311
                                                R-squared         =     0.0086
                                                Root MSE          =     .24722

------------------------------------------------------------------------------
             |               Robust
    problemR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |  -.0075979   .0290046    -0.26   0.793     -.064581    .0493852
         rep |  -.0556833   .0300379    -1.85   0.064    -.1146966    .0033301
   treat_rep |   .0266432   .0437743     0.61   0.543    -.0593569    .1126434
       _cons |   .6982759    .020021    34.88   0.000     .6589421    .7376096
------------------------------------------------------------------------------
(est5 stored)

. eststo: reg problemR treat rep treat_rep $control, robust 

Linear regression                               Number of obs     =        514
                                                F(9, 504)         =       1.89
                                                Prob > F          =     0.0509
                                                R-squared         =     0.0332
                                                Root MSE          =     .24559

------------------------------------------------------------------------------
             |               Robust
    problemR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |  -.0086822   .0286075    -0.30   0.762    -.0648869    .0475225
         rep |  -.0608055   .0307636    -1.98   0.049    -.1212462   -.0003647
   treat_rep |   .0182684   .0436205     0.42   0.676     -.067432    .1039688
        ageR |  -.0263795   .0442912    -0.60   0.552    -.1133977    .0606387
      female |   .0611689   .0223368     2.74   0.006     .0172841    .1050537
     incomeR |   .0011401   .0463844     0.02   0.980    -.0899905    .0922707
       white |    .027384   .0287126     0.95   0.341    -.0290272    .0837953
 religiosity |   .0218121   .0262139     0.83   0.406    -.0296898     .073314
     college |  -.0411797   .0224223    -1.84   0.067    -.0852324    .0028731
       _cons |    .665592   .0402368    16.54   0.000     .5865394    .7446445
------------------------------------------------------------------------------
(est6 stored)

. esttab using output_problem_robust.tex, ar2(2) b(2) se(2) starlevels(* 0.1 ** .05 *** .01) label replace
(output written to output_problem_robust.tex)

. eststo clear

. 
. 
. ***Generate Table B.3 Immigration Attitudes 
. 
. eststo: reg r_immR treat if rep == 1, robust 

Linear regression                               Number of obs     =        251
                                                F(1, 249)         =       8.22
                                                Prob > F          =     0.0045
                                                R-squared         =     0.0315
                                                Root MSE          =     .30312

------------------------------------------------------------------------------
             |               Robust
      r_immR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |   .1091794   .0380852     2.87   0.005     .0341692    .1841897
       _cons |   .2981481   .0272618    10.94   0.000     .2444549    .3518413
------------------------------------------------------------------------------
(est1 stored)

. eststo: reg r_immR treat $control if rep == 1, robust 

Linear regression                               Number of obs     =        251
                                                F(7, 243)         =       9.66
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1805
                                                Root MSE          =     .28224

------------------------------------------------------------------------------
             |               Robust
      r_immR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |   .1015462   .0363363     2.79   0.006     .0299718    .1731206
        ageR |  -.3907841   .0794542    -4.92   0.000     -.547291   -.2342772
      female |     -.0313   .0405308    -0.77   0.441    -.1111365    .0485364
     incomeR |  -.0433941   .0798436    -0.54   0.587     -.200668    .1138797
       white |  -.1296013    .057882    -2.24   0.026    -.2436159   -.0155868
 religiosity |   .0147184   .0480825     0.31   0.760    -.0799932      .10943
     college |    .018308   .0403803     0.45   0.651    -.0612321     .097848
       _cons |   .6115006   .0812074     7.53   0.000     .4515404    .7714609
------------------------------------------------------------------------------
(est2 stored)

. eststo: reg r_immR treat if rep == 0, robust 

Linear regression                               Number of obs     =        263
                                                F(1, 261)         =       0.03
                                                Prob > F          =     0.8719
                                                R-squared         =     0.0001
                                                Root MSE          =     .27234

------------------------------------------------------------------------------
             |               Robust
      r_immR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |   .0054208   .0335791     0.16   0.872    -.0606997    .0715413
       _cons |   .5051724   .0231516    21.82   0.000     .4595847    .5507601
------------------------------------------------------------------------------
(est3 stored)

. eststo: reg r_immR treat $control if rep == 0, robust 

Linear regression                               Number of obs     =        263
                                                F(7, 255)         =       4.05
                                                Prob > F          =     0.0003
                                                R-squared         =     0.0886
                                                Root MSE          =     .26305

------------------------------------------------------------------------------
             |               Robust
      r_immR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |  -.0058562   .0328358    -0.18   0.859    -.0705201    .0588078
        ageR |   -.183769   .0742564    -2.47   0.014     -.330003    -.037535
      female |  -.0760906   .0325813    -2.34   0.020    -.1402534   -.0119279
     incomeR |    .006896   .0644377     0.11   0.915    -.1200019    .1337938
       white |  -.0579827   .0377666    -1.54   0.126    -.1323568    .0163914
 religiosity |   -.032962   .0349537    -0.94   0.347    -.1017968    .0358728
     college |   .0941208   .0336911     2.79   0.006     .0277725    .1604691
       _cons |   .6386715   .0513103    12.45   0.000     .5376257    .7397174
------------------------------------------------------------------------------
(est4 stored)

. eststo  : reg r_immR treat rep treat_rep, robust

Linear regression                               Number of obs     =        514
                                                F(3, 510)         =      14.98
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0864
                                                Root MSE          =     .28778

------------------------------------------------------------------------------
             |               Robust
      r_immR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |   .0054208   .0335821     0.16   0.872    -.0605555    .0713971
         rep |  -.2070243   .0357654    -5.79   0.000    -.2772898   -.1367587
   treat_rep |   .1037586   .0507737     2.04   0.042     .0040072      .20351
       _cons |   .5051724   .0231537    21.82   0.000     .4596841    .5506607
------------------------------------------------------------------------------
(est5 stored)

. eststo  : reg r_immR treat rep treat_rep $control, robust 

Linear regression                               Number of obs     =        514
                                                F(9, 504)         =      15.93
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1790
                                                Root MSE          =     .27441

------------------------------------------------------------------------------
             |               Robust
      r_immR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |   -.015135   .0328629    -0.46   0.645    -.0797002    .0494302
         rep |  -.1798424    .034498    -5.21   0.000      -.24762   -.1120647
   treat_rep |   .1251178   .0486743     2.57   0.010     .0294883    .2207473
        ageR |  -.2923069   .0552555    -5.29   0.000    -.4008663   -.1837474
      female |   -.053296   .0250422    -2.13   0.034     -.102496   -.0040961
     incomeR |  -.0315618   .0496874    -0.64   0.526    -.1291818    .0660582
       white |  -.0717573   .0316993    -2.26   0.024    -.1340363   -.0094782
 religiosity |  -.0153565    .028729    -0.53   0.593    -.0717999    .0410868
     college |   .0664728   .0258707     2.57   0.010     .0156452    .1173005
       _cons |   .7003645   .0436627    16.04   0.000     .6145812    .7861477
------------------------------------------------------------------------------
(est6 stored)

. esttab using output_r_immR_robust.tex, ar2(2) b(2) se(2) starlevels(* 0.1 ** .05 *** .01) label replace
(output written to output_r_immR_robust.tex)

. eststo clear

. 
. 
. ** DID CHECK
. set more off

. eststo  : reg r_immR treat rep treat_rep, robust

Linear regression                               Number of obs     =        514
                                                F(3, 510)         =      14.98
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0864
                                                Root MSE          =     .28778

------------------------------------------------------------------------------
             |               Robust
      r_immR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |   .0054208   .0335821     0.16   0.872    -.0605555    .0713971
         rep |  -.2070243   .0357654    -5.79   0.000    -.2772898   -.1367587
   treat_rep |   .1037586   .0507737     2.04   0.042     .0040072      .20351
       _cons |   .5051724   .0231537    21.82   0.000     .4596841    .5506607
------------------------------------------------------------------------------
(est1 stored)

. eststo  : reg r_immR treat rep treat_rep $control, robust

Linear regression                               Number of obs     =        514
                                                F(9, 504)         =      15.93
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1790
                                                Root MSE          =     .27441

------------------------------------------------------------------------------
             |               Robust
      r_immR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       treat |   -.015135   .0328629    -0.46   0.645    -.0797002    .0494302
         rep |  -.1798424    .034498    -5.21   0.000      -.24762   -.1120647
   treat_rep |   .1251178   .0486743     2.57   0.010     .0294883    .2207473
        ageR |  -.2923069   .0552555    -5.29   0.000    -.4008663   -.1837474
      female |   -.053296   .0250422    -2.13   0.034     -.102496   -.0040961
     incomeR |  -.0315618   .0496874    -0.64   0.526    -.1291818    .0660582
       white |  -.0717573   .0316993    -2.26   0.024    -.1340363   -.0094782
 religiosity |  -.0153565    .028729    -0.53   0.593    -.0717999    .0410868
     college |   .0664728   .0258707     2.57   0.010     .0156452    .1173005
       _cons |   .7003645   .0436627    16.04   0.000     .6145812    .7861477
------------------------------------------------------------------------------
(est2 stored)

. esttab using did_study1.tex, ar2 b(3) se(3) starlevels(* 0.1 ** .05 *** .01) label replace
(output written to did_study1.tex)

. eststo clear

. 
. 
. 
. 
end of do-file

. do "Appendix_Study2.do"

. **** This file generates all tables and notes found in the Appendices for Study 2.
. 
. use "Study2_clean.dta", clear

. 
. 
. *** Generate Table C1 (Demographic Table): 
. 
. ***** Summary of Demographics
. su age female income white rel trump college immR wallR2 uacR hawkeyeR legalR immig_index econ_threa2 cultl_thre2_v2 outgroupr ingroupr victimr con
> cernR problemR percent_1 percent_2 if rep == 1

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |        450    42.91556     12.5681         19         81
      female |        450    .4266667    .4951435          0          1
      income |        450    6.191111    3.005401          1         14
       white |        450    .9177778    .2750087          0          1
         rel |        450    2.017778    1.784528          0          5
-------------+---------------------------------------------------------
       trump |        450    .7377778    .4403324          0          1
     college |        450    .4822222      .50024          0          1
        immR |        450    .2794444    .2570709          0          1
      wallR2 |        450    .2577778    .2955079          0          1
        uacR |        450    .3333333    .4719292          0          1
-------------+---------------------------------------------------------
    hawkeyeR |        450    .3688889    .3188696          0          1
      legalR |        450    .4503704    .3179542          0          1
 immig_index |        450     .337963    .2474146          0          1
 econ_threa2 |        450    .7414815    .2438712          0          1
cultl_t~2_v2 |        450    .6025926    .2858205          0          1
-------------+---------------------------------------------------------
   outgroupr |        450     .402963    .2719523          0          1
    ingroupr |        450    .5625926     .327485          0          1
     victimr |        450    .6437037    .3082084          0          1
    concernR |        450    .7177778    .2607714          0          1
    problemR |        450    .6677778    .2641656          0          1
-------------+---------------------------------------------------------
   percent_1 |        450    22.71778    19.50782          0        100
   percent_2 |        450    25.22889    20.93033          0        100

. su age female income white rel trump college immR wallR2 uacR hawkeyeR legalR immig_index econ_threa2 cultl_thre2_v2 outgroupr ingroupr victimr con
> cernR problemR percent_1 percent_2 if rep == 0

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |        462     38.6342    12.14564         19         88
      female |        462    .4372294    .4965819          0          1
      income |        462    5.545455    2.834765          1         14
       white |        462    .7683983    .4223132          0          1
         rel |        462    .7770563    1.353101          0          5
-------------+---------------------------------------------------------
       trump |        462    .0324675    .1774304          0          1
     college |        462    .5324675    .4994856          0          1
        immR |        462    .5876623    .2505944          0          1
      wallR2 |        462    .8290043    .2595127          0          1
        uacR |        462    .7683983    .4223132          0          1
-------------+---------------------------------------------------------
    hawkeyeR |        462    .6601732    .2307024          0          1
      legalR |        462    .7936508    .2478893          0          1
 immig_index |        462    .7277778     .208988          0          1
 econ_threa2 |        462    .3860029    .2693311          0          1
cultl_t~2_v2 |        462     .252886    .2361315          0          1
-------------+---------------------------------------------------------
   outgroupr |        462    .1533189    .2056734          0          1
    ingroupr |        462    .2467532    .2857722          0          1
     victimr |        462    .2694805    .2878587          0          1
    concernR |        462     .728355    .2514968          0          1
    problemR |        462    .6801948    .2389024          0          1
-------------+---------------------------------------------------------
   percent_1 |        460        31.8    22.72003          0         91
   percent_2 |        460    27.92174    23.05328          1        100

. 
. ***** Summary Stats of DVs by Party
. orth_out immR wallR2 uacR hawkeyeR legalR immig_index econ_threa2 cultl_thre2 outgroupr ingroupr victimr using imm.tex, by(rep) se pcompare count l
> atex replace

                                             0:            1:  (1) vs. (~e:
                                             _             _             _
           Immigration Rate:mean         0.588         0.279         0.000
                              se         0.012         0.012             .
        Mexican Border Wall:mean         0.829         0.258         0.000
                              se         0.012         0.014             .
     Unaccompanied Children:mean         0.768         0.333         0.000
                              se         0.020         0.022             .
 Illegal Immigration Policy:mean         0.660         0.369         0.000
                              se         0.011         0.015             .
        Path to Citizenship:mean         0.794         0.450         0.000
                              se         0.012         0.015             .
Immigration Attitudes Index:mean         0.728         0.338         0.000
                              se         0.010         0.012             .
            Economic Threat:mean         0.386         0.741         0.000
                              se         0.013         0.011             .
            Cultural Threat:mean         0.253         0.603         0.000
                              se         0.011         0.013             .
                   Outgroup:mean         0.153         0.403         0.000
                              se         0.010         0.013             .
                    Ingroup:mean         0.247         0.563         0.000
                              se         0.013         0.015             .
                     Victim:mean         0.269         0.644         0.000
                              se         0.013         0.015             .
                             N:_       462.000       450.000             .

. 
. 
. *** Generate Table C2 (Balance): 
. orth_out ageR female incomeR white rel trump college using balance_dem.tex if rep == 1, by(treat) se pcompare test latex replace

                           Control:  Immigration:    Smuggling:       Values:  (1) vs. (~e:  (1) vs. (~e:  (1) vs. (~e:  (2) vs. (~e:  (2) vs. (~e:
                                 _             _             _             _             _             _             _             _             _
            Age:mean         0.283         0.280         0.281         0.288         0.873         0.929         0.766         0.950         0.667
                  se         0.012         0.013         0.014         0.014             .             .             .             .             .
         Female:mean         0.484         0.398         0.387         0.430         0.200         0.140         0.409         0.874         0.637
                  se         0.045         0.048         0.046         0.047             .             .             .             .             .
         Income:mean         0.412         0.423         0.403         0.361         0.719         0.786         0.082         0.554         0.045
                  se         0.020         0.023         0.023         0.021             .             .             .             .             .
          White:mean         0.934         0.874         0.946         0.912         0.120         0.713         0.524         0.064         0.360
                  se         0.023         0.033         0.022         0.027             .             .             .             .             .
    Religiosity:mean         1.918         1.990         2.000         2.167         0.763         0.717         0.288         0.968         0.485
                  se         0.156         0.183         0.163         0.174             .             .             .             .             .
Voted For Trump:mean         0.779         0.806         0.631         0.737         0.620         0.013         0.455         0.004         0.230
                  se         0.038         0.039         0.046         0.041             .             .             .             .             .
 College Degree:mean         0.525         0.456         0.495         0.447         0.310         0.659         0.237         0.568         0.895
                  se         0.045         0.049         0.048         0.047             .             .             .             .             .

                       (3) vs. (~e:  p-value f~y:
                                 _             _
            Age:mean         0.719         0.973
                  se             .             .
         Female:mean         0.520         0.448
                  se             .             .
         Income:mean         0.176         0.206
                  se             .             .
          White:mean         0.328         0.232
                  se             .             .
    Religiosity:mean         0.486         0.752
                  se             .             .
Voted For Trump:mean         0.087         0.017
                  se             .             .
 College Degree:mean         0.472         0.620
                  se             .             .

. orth_out ageR female incomeR white rel trump college using balance_rep.tex if rep == 0, by(treat) se pcompare test latex replace

                           Control:  Immigration:    Smuggling:       Values:  (1) vs. (~e:  (1) vs. (~e:  (1) vs. (~e:  (2) vs. (~e:  (2) vs. (~e:
                                 _             _             _             _             _             _             _             _             _
            Age:mean         0.218         0.242         0.240         0.236         0.185         0.250         0.357         0.866         0.709
                  se         0.013         0.012         0.013         0.013             .             .             .             .             .
         Female:mean         0.491         0.430         0.458         0.376         0.361         0.624         0.085         0.666         0.401
                  se         0.049         0.045         0.046         0.045             .             .             .             .             .
         Income:mean         0.343         0.371         0.346         0.337         0.324         0.898         0.852         0.393         0.244
                  se         0.020         0.021         0.020         0.020             .             .             .             .             .
          White:mean         0.783         0.793         0.763         0.735         0.849         0.719         0.406         0.570         0.291
                  se         0.040         0.037         0.039         0.041             .             .             .             .             .
    Religiosity:mean         0.774         0.860         0.602         0.872         0.649         0.319         0.592         0.139         0.947
                  se         0.133         0.133         0.111         0.126             .             .             .             .             .
Voted For Trump:mean         0.028         0.000         0.051         0.051         0.063         0.393         0.386         0.012         0.012
                  se         0.016         0.000         0.020         0.020             .             .             .             .             .
 College Degree:mean         0.528         0.529         0.551         0.521         0.993         0.737         0.918         0.735         0.908
                  se         0.049         0.046         0.046         0.046             .             .             .             .             .

                       (3) vs. (~e:  p-value f~y:
                                 _             _
            Age:mean         0.836         0.570
                  se             .             .
         Female:mean         0.207         0.359
                  se             .             .
         Income:mean         0.756         0.636
                  se             .             .
          White:mean         0.627         0.730
                  se             .             .
    Religiosity:mean         0.109         0.392
                  se             .             .
Voted For Trump:mean         0.988         0.082
                  se             .             .
 College Degree:mean         0.652         0.973
                  se             .             .

. 
. 
. ************ Generate data for note on K-Smirnov test
. 
. ** Ksmirnov
. ksmirnov immig_index, by(rep)

Two-sample Kolmogorov-Smirnov test for equality of distribution functions

 Smaller group       D       P-value  
 -----------------------------------
 0:                  0.0000    1.000
 1:                 -0.6056    0.000
 Combined K-S:       0.6056    0.000

Note: Ties exist in combined dataset;
      there are 60 unique values out of 912 observations.

. /*
>  0:                  0.0000    1.000
>  1:                 -0.6056    0.000
>  Combined K-S:       0.6056    0.000
>  P-Value < 0.000
> */
. ksmirnov concernR, by(rep)

Two-sample Kolmogorov-Smirnov test for equality of distribution functions

 Smaller group       D       P-value  
 -----------------------------------
 0:                  0.0040    0.993
 1:                 -0.0266    0.724
 Combined K-S:       0.0266    0.997

Note: Ties exist in combined dataset;
      there are 5 unique values out of 912 observations.

. /*
>  0:                  0.0040    0.993
>  1:                 -0.0266    0.724
>  Combined K-S:       0.0266    0.997
>  P-Value = 0.997
> */
. 
. 
. *** Generate Table D1 (Human Trafficking Attitudes): 
. eststo  : reg problemR treat22 treat23 treat24 trump if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =       1.06
                                                Prob > F          =     0.3758
                                                R-squared         =     0.0095
                                                Root MSE          =     .26409

------------------------------------------------------------------------------
             |               Robust
    problemR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0145303   .0349275     0.42   0.678    -.0541131    .0831737
     treat23 |  -.0019212   .0344969    -0.06   0.956    -.0697183    .0658759
     treat24 |  -.0387414   .0353759    -1.10   0.274     -.108266    .0307832
       trump |   .0364006   .0288284     1.26   0.207    -.0202562    .0930574
       _cons |   .6478848   .0329447    19.67   0.000     .5831382    .7126313
------------------------------------------------------------------------------
(est1 stored)

. eststo  : reg problemR treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(10, 439)        =       4.93
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0981
                                                Root MSE          =     .25371

------------------------------------------------------------------------------
             |               Robust
    problemR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0023977   .0338839     0.07   0.944    -.0641972    .0689926
     treat23 |  -.0183261   .0323079    -0.57   0.571    -.0818234    .0451712
     treat24 |  -.0537137   .0348345    -1.54   0.124    -.1221768    .0147495
        ageR |   .1336561     .08525     1.57   0.118    -.0338927    .3012049
      female |  -.1282299   .0259804    -4.94   0.000    -.1792914   -.0771685
     incomeR |  -.0455565   .0548895    -0.83   0.407    -.1534353    .0623223
       white |  -.0354805   .0495023    -0.72   0.474    -.1327714    .0618104
         rel |   .0164786    .007225     2.28   0.023     .0022787    .0306785
       trump |   .0143751   .0274991     0.52   0.601    -.0396712    .0684214
     college |   .0101902   .0256317     0.40   0.691    -.0401859    .0605663
       _cons |    .704211   .0673114    10.46   0.000     .5719183    .8365038
------------------------------------------------------------------------------
(est2 stored)

. eststo  : reg concernR treat22 treat23 treat24 trump if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =       0.58
                                                Prob > F          =     0.6745
                                                R-squared         =     0.0051
                                                Root MSE          =     .26127

------------------------------------------------------------------------------
             |               Robust
    concernR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0156442    .035507     0.44   0.660     -.054138    .0854264
     treat23 |  -.0268555   .0340138    -0.79   0.430    -.0937032    .0399922
     treat24 |  -.0284909   .0346505    -0.82   0.411    -.0965898     .039608
       trump |  -.0141781   .0273763    -0.52   0.605    -.0679809    .0396248
       _cons |   .7384993   .0307189    24.04   0.000     .6781272    .7988714
------------------------------------------------------------------------------
(est3 stored)

. eststo  : reg concernR treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(10, 439)        =       5.18
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1020
                                                Root MSE          =     .24992

------------------------------------------------------------------------------
             |               Robust
    concernR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0045983   .0328116     0.14   0.889    -.0598891    .0690856
     treat23 |  -.0436476   .0329897    -1.32   0.187     -.108485    .0211898
     treat24 |  -.0465202   .0339727    -1.37   0.172    -.1132895    .0202491
        ageR |   .1379187   .0815949     1.69   0.092    -.0224465     .298284
      female |  -.0906441   .0254894    -3.56   0.000    -.1407404   -.0405477
     incomeR |  -.0116609   .0546526    -0.21   0.831    -.1190742    .0957524
       white |   .0073485   .0473249     0.16   0.877     -.085663      .10036
         rel |   .0297193   .0069225     4.29   0.000      .016114    .0433247
       trump |  -.0441227   .0270025    -1.63   0.103    -.0971931    .0089476
     college |  -.0428908   .0239819    -1.79   0.074    -.0900243    .0042428
       _cons |   .7300833   .0656295    11.12   0.000     .6010962    .8590703
------------------------------------------------------------------------------
(est4 stored)

. 
. eststo  : reg problemR treat22 treat23 treat24 trump if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =       4.37
                                                Prob > F          =     0.0018
                                                R-squared         =     0.0371
                                                Root MSE          =     .23545

------------------------------------------------------------------------------
             |               Robust
    problemR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0519842   .0308216     1.69   0.092    -.0085854    .1125538
     treat23 |   .0016797   .0318211     0.05   0.958    -.0608542    .0642136
     treat24 |  -.0693691   .0335689    -2.07   0.039    -.1353375   -.0034006
       trump |  -.0585434   .0746397    -0.78   0.433    -.2052231    .0881363
       _cons |   .6856192   .0239058    28.68   0.000     .6386403     .732598
------------------------------------------------------------------------------
(est5 stored)

. eststo  : reg problemR treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(10, 451)        =       4.90
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0890
                                                Root MSE          =     .23054

------------------------------------------------------------------------------
             |               Robust
    problemR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0480528   .0302836     1.59   0.113    -.0114616    .1075672
     treat23 |   .0007101   .0310387     0.02   0.982    -.0602882    .0617085
     treat24 |  -.0825223   .0335713    -2.46   0.014    -.1484978   -.0165468
        ageR |  -.0164158   .0819866    -0.20   0.841     -.177539    .1447074
      female |  -.0967875   .0224192    -4.32   0.000    -.1408465   -.0527286
     incomeR |  -.0797716   .0513887    -1.55   0.121    -.1807625    .0212194
       white |   -.019722   .0277385    -0.71   0.477    -.0742347    .0347907
         rel |   .0101247   .0083362     1.21   0.225     -.006258    .0265074
       trump |  -.0611373     .06945    -0.88   0.379    -.1976231    .0753485
     college |  -.0081576   .0228681    -0.36   0.721    -.0530989    .0367836
       _cons |   .7760019   .0442686    17.53   0.000     .6890036    .8630003
------------------------------------------------------------------------------
(est6 stored)

. eststo  : reg concernR treat22 treat23 treat24 trump if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =       4.00
                                                Prob > F          =     0.0033
                                                R-squared         =     0.0301
                                                Root MSE          =     .24877

------------------------------------------------------------------------------
             |               Robust
    concernR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0724773   .0317766     2.28   0.023      .010031    .1349236
     treat23 |   .0022512   .0346893     0.06   0.948     -.065919    .0704215
     treat24 |  -.0407132   .0339067    -1.20   0.230    -.1073456    .0259192
       trump |  -.0555263   .0677807    -0.82   0.413    -.1887269    .0776742
       _cons |   .7209111   .0244589    29.47   0.000     .6728452    .7689771
------------------------------------------------------------------------------
(est7 stored)

. eststo  : reg concernR treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(10, 451)        =       5.85
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0975
                                                Root MSE          =     .24156

------------------------------------------------------------------------------
             |               Robust
    concernR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0662988   .0310693     2.13   0.033     .0052402    .1273574
     treat23 |   .0019698   .0337381     0.06   0.953    -.0643336    .0682732
     treat24 |  -.0543154   .0332377    -1.63   0.103    -.1196353    .0110045
        ageR |   .0629874   .0875454     0.72   0.472    -.1090601     .235035
      female |  -.0955634   .0234508    -4.08   0.000    -.1416498   -.0494771
     incomeR |   -.101523   .0535516    -1.90   0.059    -.2067647    .0037187
       white |   .0020071   .0275586     0.07   0.942    -.0521521    .0561662
         rel |   .0135091   .0092765     1.46   0.146    -.0047215    .0317396
       trump |  -.0771312   .0640034    -1.21   0.229    -.2029132    .0486507
     college |  -.0434177   .0238771    -1.82   0.070    -.0903418    .0035064
       _cons |   .8003378   .0426687    18.76   0.000     .7164837    .8841919
------------------------------------------------------------------------------
(est8 stored)

. esttab using ht.tex, ar2 b(3) se(3) starlevels(* 0.1 ** .05 *** .01) label replace
(output written to ht.tex)

. eststo clear

. 
. 
. 
. *** Generate Table D2 (Immigration Attitudes for Republicans): 
. eststo  : reg immR treat22 treat23 treat24 trump if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =      11.95
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0991
                                                Root MSE          =      .2451

------------------------------------------------------------------------------
             |               Robust
        immR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0819087   .0317964     2.58   0.010      .019419    .1443985
     treat23 |   .0887724   .0322068     2.76   0.006     .0254761    .1520686
     treat24 |   .0353617   .0306709     1.15   0.250    -.0249161    .0956395
       trump |  -.1584014   .0276759    -5.72   0.000     -.212793   -.1040098
       _cons |    .346706   .0302519    11.46   0.000     .2872517    .4061603
------------------------------------------------------------------------------
(est1 stored)

. eststo  : reg immR treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(10, 439)        =       7.04
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1461
                                                Root MSE          =     .24025

------------------------------------------------------------------------------
             |               Robust
        immR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0804671    .031134     2.58   0.010     .0192768    .1416573
     treat23 |   .0887589   .0314355     2.82   0.005     .0269761    .1505417
     treat24 |   .0340534   .0305122     1.12   0.265    -.0259148    .0940216
        ageR |   -.224938   .0844588    -2.66   0.008    -.3909318   -.0589441
      female |   .0227907   .0244567     0.93   0.352    -.0252761    .0708576
     incomeR |   .0481035   .0524284     0.92   0.359    -.0549384    .1511455
       white |   -.009066   .0376341    -0.24   0.810    -.0830314    .0648994
         rel |   .0237219   .0068553     3.46   0.001     .0102485    .0371953
       trump |  -.1610163   .0273396    -5.89   0.000    -.2147491   -.1072835
     college |   -.000304   .0239485    -0.01   0.990    -.0473719     .046764
       _cons |    .344656   .0570391     6.04   0.000     .2325522    .4567597
------------------------------------------------------------------------------
(est2 stored)

. eststo  : reg wallR2 treat22 treat23 treat24 trump if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =      29.87
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2625
                                                Root MSE          =     .25491

------------------------------------------------------------------------------
             |               Robust
      wallR2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0873625    .036843     2.37   0.018     .0149546    .1597704
     treat23 |   .0248959   .0329221     0.76   0.450    -.0398062     .089598
     treat24 |    .018289   .0320011     0.57   0.568     -.044603    .0811811
       trump |  -.3395809   .0327449   -10.37   0.000    -.4039348   -.2752269
       _cons |   .4775425   .0381878    12.51   0.000     .4024917    .5525933
------------------------------------------------------------------------------
(est3 stored)

. eststo  : reg wallR2 treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(10, 439)        =      15.12
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2847
                                                Root MSE          =     .25275

------------------------------------------------------------------------------
             |               Robust
      wallR2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0836015   .0368103     2.27   0.024     .0112551    .1559478
     treat23 |   .0250419   .0323859     0.77   0.440    -.0386088    .0886927
     treat24 |   .0203698   .0320111     0.64   0.525    -.0425442    .0832839
        ageR |   -.224913   .0895372    -2.51   0.012    -.4008878   -.0489382
      female |   .0113846   .0254651     0.45   0.655     -.038664    .0614332
     incomeR |   .0935739   .0539993     1.73   0.084    -.0125553    .1997031
       white |  -.0136542    .052309    -0.26   0.794    -.1164615     .089153
         rel |   .0101137   .0068245     1.48   0.139     -.003299    .0235263
       trump |  -.3398967    .032206   -10.55   0.000    -.4031937   -.2765997
     college |  -.0220866   .0261782    -0.84   0.399    -.0735368    .0293635
       _cons |   .5023052   .0666467     7.54   0.000     .3713189    .6332915
------------------------------------------------------------------------------
(est4 stored)

. eststo  : reg uacR treat22 treat23 treat24 trump if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =       9.15
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0818
                                                Root MSE          =     .45423

------------------------------------------------------------------------------
             |               Robust
        uacR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0998992    .060364     1.65   0.099    -.0187346    .2185331
     treat23 |   .0200342   .0601947     0.33   0.739    -.0982671    .1383354
     treat24 |   .0251181   .0577516     0.43   0.664    -.0883816    .1386178
       trump |  -.3000984    .052096    -5.76   0.000    -.4024831   -.1977136
       _cons |   .5205684   .0588394     8.85   0.000     .4049308     .636206
------------------------------------------------------------------------------
(est5 stored)

. eststo  : reg uacR treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(10, 439)        =       4.39
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0926
                                                Root MSE          =     .45463

------------------------------------------------------------------------------
             |               Robust
        uacR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0897069   .0609632     1.47   0.142    -.0301091     .209523
     treat23 |   .0161817   .0606909     0.27   0.790    -.1030991    .1354626
     treat24 |   .0202255   .0582118     0.35   0.728     -.094183     .134634
        ageR |  -.2400144   .1493127    -1.61   0.109     -.533471    .0534422
      female |  -.0290503   .0459145    -0.63   0.527    -.1192898    .0611892
     incomeR |   .0261279   .0958436     0.27   0.785    -.1622414    .2144972
       white |  -.0789748   .0799285    -0.99   0.324    -.2360648    .0781152
         rel |   .0112765   .0126263     0.89   0.372    -.0135389     .036092
       trump |  -.3025041   .0528218    -5.73   0.000    -.4063191   -.1986891
     college |  -.0174061   .0454807    -0.38   0.702    -.1067931    .0719809
       _cons |   .6549044   .1134938     5.77   0.000     .4318457    .8779632
------------------------------------------------------------------------------
(est6 stored)

. eststo  : reg hawkeyeR treat22 treat23 treat24 trump if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =       5.71
                                                Prob > F          =     0.0002
                                                R-squared         =     0.0478
                                                Root MSE          =     .31255

------------------------------------------------------------------------------
             |               Robust
    hawkeyeR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0418414   .0422284     0.99   0.322    -.0411506    .1248333
     treat23 |   .0170615   .0412679     0.41   0.679    -.0640427    .0981657
     treat24 |    .017641   .0406859     0.43   0.665    -.0623193    .0976013
       trump |  -.1557537   .0336533    -4.63   0.000    -.2218929   -.0896146
       _cons |   .4655459    .038891    11.97   0.000     .3891131    .5419788
------------------------------------------------------------------------------
(est7 stored)

. eststo  : reg hawkeyeR treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(10, 439)        =       3.98
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0742
                                                Root MSE          =     .31029

------------------------------------------------------------------------------
             |               Robust
    hawkeyeR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |    .033893   .0420498     0.81   0.421     -.048751     .116537
     treat23 |   .0098189   .0411113     0.24   0.811    -.0709805    .0906183
     treat24 |   .0120446   .0400831     0.30   0.764    -.0667341    .0908232
        ageR |   .0035036   .0993621     0.04   0.972     -.191781    .1987882
      female |  -.0426994   .0311216    -1.37   0.171    -.1038652    .0184665
     incomeR |   .0772619   .0655114     1.18   0.239    -.0514931    .2060168
       white |  -.0305089   .0536988    -0.57   0.570    -.1360476    .0750299
         rel |   .0218286   .0086992     2.51   0.012     .0047314    .0389257
       trump |  -.1704033   .0337849    -5.04   0.000    -.2368036    -.104003
     college |  -.0062654    .031293    -0.20   0.841     -.067768    .0552373
       _cons |   .4547287   .0749944     6.06   0.000     .3073359    .6021214
------------------------------------------------------------------------------
(est8 stored)

. eststo  : reg legalR treat22 treat23 treat24 trump if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =       8.04
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0713
                                                Root MSE          =     .30779

------------------------------------------------------------------------------
             |               Robust
      legalR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0506305   .0406487     1.25   0.214    -.0292568    .1305179
     treat23 |  -.0081715   .0416219    -0.20   0.844    -.0899714    .0736285
     treat24 |  -.0266784   .0408368    -0.65   0.514    -.1069354    .0535785
       trump |  -.1873605   .0349775    -5.36   0.000    -.2561022   -.1186189
       _cons |   .5857862   .0416426    14.07   0.000     .5039457    .6676268
------------------------------------------------------------------------------
(est9 stored)

. eststo  : reg legalR treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(10, 439)        =       4.67
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0920
                                                Root MSE          =     .30641

------------------------------------------------------------------------------
             |               Robust
      legalR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0402738   .0409273     0.98   0.326     -.040164    .1207117
     treat23 |  -.0145761   .0416051    -0.35   0.726     -.096346    .0671938
     treat24 |  -.0340798    .040635    -0.84   0.402     -.113943    .0457834
        ageR |   -.071798   .0967064    -0.74   0.458     -.261863    .1182671
      female |  -.0288896   .0308927    -0.94   0.350    -.0896055    .0318264
     incomeR |   .0647288   .0673672     0.96   0.337    -.0676736    .1971311
       white |  -.0510499   .0468309    -1.09   0.276    -.1430905    .0409907
         rel |   .0185559   .0087257     2.13   0.034     .0014065    .0357053
       trump |  -.2001273   .0348319    -5.75   0.000    -.2685854   -.1316693
     college |  -.0421412   .0309879    -1.36   0.175    -.1030443    .0187619
       _cons |     .63757   .0709448     8.99   0.000     .4981363    .7770037
------------------------------------------------------------------------------
(est10 stored)

. eststo  : reg immig_index treat22 treat23 treat24 trump if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =      20.78
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1739
                                                Root MSE          =     .22588

------------------------------------------------------------------------------
             |               Robust
 immig_index |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0723285   .0294754     2.45   0.015     .0144003    .1302566
     treat23 |   .0285185   .0303451     0.94   0.348    -.0311189    .0881559
     treat24 |   .0139463   .0296187     0.47   0.638    -.0442637    .0721563
       trump |   -.228239   .0269447    -8.47   0.000    -.2811936   -.1752844
       _cons |   .4792298   .0313787    15.27   0.000     .4175609    .5408987
------------------------------------------------------------------------------
(est11 stored)

. eststo  : reg immig_index treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(10, 439)        =      10.73
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2039
                                                Root MSE          =     .22326

------------------------------------------------------------------------------
             |               Robust
 immig_index |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0655885    .029666     2.21   0.028     .0072835    .1238935
     treat23 |   .0250451   .0302419     0.83   0.408    -.0343919     .084482
     treat24 |   .0105227   .0294063     0.36   0.721    -.0472718    .0683172
        ageR |   -.151632   .0723528    -2.10   0.037    -.2938328   -.0094311
      female |  -.0132928   .0227524    -0.58   0.559    -.0580099    .0314244
     incomeR |   .0619592   .0476074     1.30   0.194    -.0316075    .1555259
       white |  -.0366508   .0366622    -1.00   0.318     -.108706    .0354044
         rel |   .0170993   .0063197     2.71   0.007     .0046787      .02952
       trump |  -.2347895   .0267401    -8.78   0.000     -.287344    -.182235
     college |  -.0176406   .0226922    -0.78   0.437    -.0622395    .0269582
       _cons |   .5188328   .0518186    10.01   0.000     .4169895    .6206762
------------------------------------------------------------------------------
(est12 stored)

. esttab using immigration_rep.tex, ar2 b(3) se(3) starlevels(* 0.1 ** .05 *** .01) label replace
(output written to immigration_rep.tex)

. eststo clear

. 
. 
. * Generate Table D3 (Immigration Attitudes for Democrats): 
. eststo  : reg immR treat22 treat23 treat24 trump if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =       9.43
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0749
                                                Root MSE          =     .24208

------------------------------------------------------------------------------
             |               Robust
        immR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |    .083348   .0319513     2.61   0.009     .0205582    .1461378
     treat23 |   .1196946   .0328269     3.65   0.000     .0551843     .184205
     treat24 |   .0227566   .0321934     0.71   0.480    -.0405089    .0860221
       trump |  -.2788666   .0674622    -4.13   0.000    -.4114413    -.146292
       _cons |   .5385528   .0235332    22.88   0.000     .4923062    .5847995
------------------------------------------------------------------------------
(est1 stored)

. eststo  : reg immR treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(10, 451)        =       6.13
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1066
                                                Root MSE          =     .23948

------------------------------------------------------------------------------
             |               Robust
        immR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |    .089129   .0315251     2.83   0.005     .0271746    .1510833
     treat23 |   .1226064   .0325353     3.77   0.000     .0586668     .186546
     treat24 |   .0288769   .0319125     0.90   0.366    -.0338388    .0915926
        ageR |  -.2517416   .0861584    -2.92   0.004    -.4210634   -.0824197
      female |  -.0119064   .0224993    -0.53   0.597     -.056123    .0323101
     incomeR |   .0137612   .0522494     0.26   0.792    -.0889212    .1164437
       white |   .0449562   .0268067     1.68   0.094    -.0077254    .0976378
         rel |  -.0102473   .0088337    -1.16   0.247    -.0276077    .0071131
       trump |  -.2634084    .069798    -3.77   0.000    -.4005781   -.1262387
     college |   .0340644   .0233016     1.46   0.144    -.0117288    .0798575
       _cons |    .548946   .0440962    12.45   0.000     .4622865    .6356055
------------------------------------------------------------------------------
(est2 stored)

. eststo  : reg wallR2 treat22 treat23 treat24 trump if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =      27.08
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1412
                                                Root MSE          =     .24154

------------------------------------------------------------------------------
             |               Robust
      wallR2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0097492   .0321757    -0.30   0.762    -.0729799    .0534814
     treat23 |   .0474778    .031667     1.50   0.134    -.0147531    .1097087
     treat24 |   .0037485   .0334914     0.11   0.911    -.0620678    .0695648
       trump |  -.5455749   .0528673   -10.32   0.000    -.6494681   -.4416818
       _cons |   .8361955   .0236238    35.40   0.000     .7897707    .8826203
------------------------------------------------------------------------------
(est3 stored)

. eststo  : reg wallR2 treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(10, 451)        =      15.18
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1865
                                                Root MSE          =     .23665

------------------------------------------------------------------------------
             |               Robust
      wallR2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0072774   .0323486    -0.22   0.822    -.0708501    .0562953
     treat23 |   .0409137   .0319708     1.28   0.201    -.0219165    .1037439
     treat24 |   .0061188   .0333917     0.18   0.855    -.0595038    .0717414
        ageR |  -.0835614   .0975195    -0.86   0.392    -.2752104    .1080876
      female |  -.0307388   .0232321    -1.32   0.186    -.0763955    .0149179
     incomeR |   .0465225   .0496069     0.94   0.349    -.0509669    .1440119
       white |   .0189266   .0264194     0.72   0.474    -.0329937     .070847
         rel |  -.0372232    .009711    -3.83   0.000    -.0563076   -.0181387
       trump |  -.5216225   .0524703    -9.94   0.000     -.624739   -.4185059
     college |   .0263615    .022996     1.15   0.252    -.0188311     .071554
       _cons |   .8529581   .0391603    21.78   0.000     .7759988    .9299175
------------------------------------------------------------------------------
(est4 stored)

. eststo  : reg uacR treat22 treat23 treat24 trump if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =       4.87
                                                Prob > F          =     0.0007
                                                R-squared         =     0.0498
                                                Root MSE          =     .41346

------------------------------------------------------------------------------
             |               Robust
        uacR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0344319   .0574709     0.60   0.549    -.0785081    .1473719
     treat23 |   .0556361   .0569089     0.98   0.329    -.0561995    .1674717
     treat24 |   .0454337   .0574862     0.79   0.430    -.0675364    .1584038
       trump |  -.5244533   .1200777    -4.37   0.000    -.7604262   -.2884805
       _cons |   .7506921   .0435132    17.25   0.000     .6651813    .8362029
------------------------------------------------------------------------------
(est5 stored)

. eststo  : reg uacR treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(10, 451)        =       4.15
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0855
                                                Root MSE          =     .40832

------------------------------------------------------------------------------
             |               Robust
        uacR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0470358   .0571327     0.82   0.411    -.0652435     .159315
     treat23 |   .0578455   .0565568     1.02   0.307    -.0533021    .1689931
     treat24 |   .0452498   .0565351     0.80   0.424    -.0658551    .1563547
        ageR |  -.4145108   .1500603    -2.76   0.006    -.7094149   -.1196066
      female |  -.0739545   .0396048    -1.87   0.063    -.1517873    .0038784
     incomeR |  -.1764958   .0938513    -1.88   0.061    -.3609359    .0079443
       white |    .025581     .04643     0.55   0.582     -.065665    .1168269
         rel |  -.0122125   .0145108    -0.84   0.400    -.0407297    .0163048
       trump |  -.4781981   .1180709    -4.05   0.000    -.7102356   -.2461606
     college |   .0944892   .0403501     2.34   0.020     .0151917    .1737867
       _cons |   .8761337   .0728387    12.03   0.000     .7329884    1.019279
------------------------------------------------------------------------------
(est6 stored)

. eststo  : reg hawkeyeR treat22 treat23 treat24 trump if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =       1.87
                                                Prob > F          =     0.1143
                                                R-squared         =     0.0234
                                                Root MSE          =     .22899

------------------------------------------------------------------------------
             |               Robust
    hawkeyeR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0032665   .0298322    -0.11   0.913    -.0618917    .0553587
     treat23 |   .0368273   .0317036     1.16   0.246    -.0254757    .0991303
     treat24 |   .0057132   .0311226     0.18   0.854    -.0554479    .0668743
       trump |  -.1842863   .0782619    -2.35   0.019    -.3380841   -.0304886
       _cons |   .6561591   .0227071    28.90   0.000     .6115358    .7007823
------------------------------------------------------------------------------
(est7 stored)

. eststo  : reg hawkeyeR treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(10, 451)        =       2.16
                                                Prob > F          =     0.0191
                                                R-squared         =     0.0507
                                                Root MSE          =     .22726

------------------------------------------------------------------------------
             |               Robust
    hawkeyeR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0040301   .0297221    -0.14   0.892    -.0624411    .0543808
     treat23 |    .033029   .0317186     1.04   0.298    -.0293055    .0953636
     treat24 |   .0085378   .0311341     0.27   0.784    -.0526482    .0697238
        ageR |  -.0213608   .0799779    -0.27   0.790    -.1785364    .1358148
      female |  -.0143166   .0226144    -0.63   0.527    -.0587592     .030126
     incomeR |   .0769067   .0504671     1.52   0.128    -.0222731    .1760866
       white |   .0308894   .0266164     1.16   0.246    -.0214181    .0831969
         rel |  -.0233751   .0087433    -2.67   0.008    -.0405578   -.0061924
       trump |  -.1802354   .0788384    -2.29   0.023    -.3351717   -.0252991
     college |   .0007502   .0218254     0.03   0.973    -.0421419    .0436423
       _cons |   .6348891   .0424147    14.97   0.000     .5515341    .7182441
------------------------------------------------------------------------------
(est8 stored)

. eststo  : reg legalR treat22 treat23 treat24 trump if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =       6.07
                                                Prob > F          =     0.0001
                                                R-squared         =     0.0699
                                                Root MSE          =     .24012

------------------------------------------------------------------------------
             |               Robust
      legalR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0089983   .0303747     0.30   0.767    -.0506931    .0686897
     treat23 |   .0338273   .0307313     1.10   0.272    -.0265649    .0942196
     treat24 |   .0294482   .0302982     0.97   0.332     -.030093    .0889893
       trump |  -.3680107   .0770171    -4.78   0.000    -.5193622   -.2166592
       _cons |    .787145   .0202623    38.85   0.000     .7473262    .8269637
------------------------------------------------------------------------------
(est9 stored)

. eststo  : reg legalR treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(10, 451)        =       3.93
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0973
                                                Root MSE          =     .23812

------------------------------------------------------------------------------
             |               Robust
      legalR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0043692   .0306622     0.14   0.887    -.0558893    .0646277
     treat23 |   .0295143   .0310056     0.95   0.342    -.0314189    .0904476
     treat24 |   .0270001   .0302856     0.89   0.373    -.0325183    .0865186
        ageR |  -.0138942   .0842461    -0.16   0.869    -.1794578    .1516694
      female |  -.0526727   .0234804    -2.24   0.025    -.0988172   -.0065282
     incomeR |   .0989741   .0546517     1.81   0.071    -.0084295    .2063778
       white |   .0261473   .0284836     0.92   0.359    -.0298298    .0821243
         rel |  -.0152399   .0085323    -1.79   0.075    -.0320078    .0015281
       trump |  -.3660375   .0774104    -4.73   0.000    -.5181674   -.2139077
     college |   .0168261   .0237105     0.71   0.478    -.0297707    .0634228
       _cons |   .7644878   .0411177    18.59   0.000     .6836817    .8452939
------------------------------------------------------------------------------
(est10 stored)

. eststo  : reg immig_index treat22 treat23 treat24 trump if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =      12.76
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1110
                                                Root MSE          =     .19791

------------------------------------------------------------------------------
             |               Robust
 immig_index |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0227525   .0249204     0.91   0.362    -.0262204    .0717253
     treat23 |   .0586926   .0265983     2.21   0.028     .0064224    .1109628
     treat24 |     .02142   .0267235     0.80   0.423    -.0310961    .0739362
       trump |  -.3802384   .0557099    -6.83   0.000    -.4897177   -.2707591
       _cons |   .7137489    .018472    38.64   0.000     .6774482    .7500495
------------------------------------------------------------------------------
(est11 stored)

. eststo  : reg immig_index treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(10, 451)        =       7.90
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1522
                                                Root MSE          =     .19455

------------------------------------------------------------------------------
             |               Robust
 immig_index |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0258453   .0249254     1.04   0.300    -.0231391    .0748297
     treat23 |   .0567818   .0266059     2.13   0.033      .004495    .1090686
     treat24 |   .0231567   .0264807     0.87   0.382    -.0288841    .0751975
        ageR |  -.1570138    .071716    -2.19   0.029    -.2979528   -.0160748
      female |  -.0367178   .0190796    -1.92   0.055    -.0742138    .0007783
     incomeR |   .0119338   .0436289     0.27   0.785    -.0738073    .0976749
       white |   .0293001   .0229089     1.28   0.202    -.0157214    .0743216
         rel |  -.0196596   .0066045    -2.98   0.003    -.0326389   -.0066802
       trump |  -.3619004   .0568444    -6.37   0.000    -.4736131   -.2501877
     college |   .0344983   .0188141     1.83   0.067    -.0024759    .0714724
       _cons |   .7354829   .0341277    21.55   0.000     .6684139     .802552
------------------------------------------------------------------------------
(est12 stored)

. esttab using immigration_dem.tex, ar2 b(3) se(3) starlevels(* 0.1 ** .05 *** .01) label replace
(output written to immigration_dem.tex)

. eststo clear

. 
. *** Generate Table D4 (Support for Immigration by Party): 
. gen treat22_rep = treat22*rep
(75 missing values generated)

. gen treat23_rep = treat23*rep
(75 missing values generated)

. gen treat24_rep = treat24*rep
(75 missing values generated)

. 
. set more off

. eststo  : reg immig_index treat22 treat23 treat24 rep treat22_rep treat23_rep treat24_rep trump, robust

Linear regression                               Number of obs     =        912
                                                F(8, 903)         =     122.09
                                                Prob > F          =     0.0000
                                                R-squared         =     0.5029
                                                Root MSE          =     .21279

------------------------------------------------------------------------------
             |               Robust
 immig_index |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0264354   .0248155     1.07   0.287    -.0222674    .0751383
     treat23 |   .0557588   .0267247     2.09   0.037     .0033091    .1082084
     treat24 |   .0184296   .0267238     0.69   0.491    -.0340183    .0708776
         rep |  -.2138065   .0348117    -6.14   0.000    -.2821277   -.1454853
 treat22_rep |   .0464865   .0385894     1.20   0.229    -.0292489    .1222219
 treat23_rep |  -.0304782   .0404248    -0.75   0.451    -.1098158    .0488593
 treat24_rep |  -.0053985   .0399253    -0.14   0.892    -.0837556    .0729586
       trump |  -.2501086   .0248864   -10.05   0.000    -.2989506   -.2012667
       _cons |    .710066   .0183376    38.72   0.000     .6740766    .7460553
------------------------------------------------------------------------------
(est1 stored)

. eststo  : reg immig_index treat22 treat23 treat24 rep treat22_rep treat23_rep treat24_rep trump female incomeR white rel college, robust

Linear regression                               Number of obs     =        912
                                                F(13, 898)        =      77.15
                                                Prob > F          =     0.0000
                                                R-squared         =     0.5065
                                                Root MSE          =     .21262

------------------------------------------------------------------------------
             |               Robust
 immig_index |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0235922   .0248099     0.95   0.342    -.0250999    .0722842
     treat23 |   .0549341   .0267989     2.05   0.041     .0023383    .1075299
     treat24 |   .0163056   .0267362     0.61   0.542    -.0361671    .0687784
         rep |  -.2176724   .0349498    -6.23   0.000    -.2862652   -.1490797
 treat22_rep |   .0481656   .0386467     1.25   0.213    -.0276827    .1240139
 treat23_rep |  -.0316051   .0405875    -0.78   0.436    -.1112625    .0480523
 treat24_rep |  -.0016212   .0399198    -0.04   0.968    -.0799682    .0767259
       trump |   -.252187   .0249728   -10.10   0.000    -.3011988   -.2031752
      female |  -.0230537   .0148759    -1.55   0.122    -.0522492    .0061419
     incomeR |   .0416495    .032528     1.28   0.201    -.0221903    .1054893
       white |   .0059402   .0196972     0.30   0.763    -.0327177    .0445981
         rel |   .0013411   .0047488     0.28   0.778    -.0079789    .0106612
     college |   .0138465   .0149046     0.93   0.353    -.0154054    .0430984
       _cons |   .6941642   .0273819    25.35   0.000     .6404242    .7479043
------------------------------------------------------------------------------
(est2 stored)

. esttab using did.tex, ar2 b(3) se(3) starlevels(* 0.1 ** .05 *** .01) label replace
(output written to did.tex)

. eststo clear

. 
. 
. *** Generate Table D5 (Threat Attitudes by Party)
. 
. eststo  : reg econ_threa2 treat22 treat23 treat24 trump if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =       8.52
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0733
                                                Root MSE          =     .23582

------------------------------------------------------------------------------
             |               Robust
 econ_threa2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0724354   .0312333    -2.32   0.021    -.1338185   -.0110522
     treat23 |  -.0668986   .0299517    -2.23   0.026     -.125763   -.0080341
     treat24 |  -.0170711   .0299205    -0.57   0.569    -.0758741    .0417318
       trump |   .1287081   .0266099     4.84   0.000     .0764113    .1810048
       _cons |   .6839295    .028962    23.61   0.000     .6270102    .7408488
------------------------------------------------------------------------------
(est1 stored)

. eststo  : reg econ_threa2 treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(10, 439)        =       4.61
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0852
                                                Root MSE          =     .23589

------------------------------------------------------------------------------
             |               Robust
 econ_threa2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0710195    .031211    -2.28   0.023     -.132361   -.0096779
     treat23 |  -.0685454   .0303183    -2.26   0.024    -.1281325   -.0089584
     treat24 |  -.0140665   .0304421    -0.46   0.644    -.0738968    .0457638
        ageR |   .0422863   .0878883     0.48   0.631    -.1304477    .2150204
      female |  -.0155177   .0250332    -0.62   0.536    -.0647175    .0336821
     incomeR |    .034206   .0513407     0.67   0.506    -.0666982    .1351102
       white |   .0546145   .0427692     1.28   0.202    -.0294433    .1386723
         rel |  -.0095565   .0065985    -1.45   0.148    -.0225251     .003412
       trump |    .127222   .0273633     4.65   0.000     .0734427    .1810013
     college |  -.0153192   .0245793    -0.62   0.533     -.063627    .0329886
       _cons |   .6418824   .0615216    10.43   0.000     .5209689    .7627959
------------------------------------------------------------------------------
(est2 stored)

. eststo  : reg cultl_thre2_v2 treat22 treat23 treat24 trump if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =       6.70
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0557
                                                Root MSE          =       .279

------------------------------------------------------------------------------
             |               Robust
cultl_t~2_v2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0214311   .0387438    -0.55   0.580    -.0975747    .0547125
     treat23 |  -.0148694   .0354442    -0.42   0.675    -.0845282    .0547895
     treat24 |    .041224   .0381295     1.08   0.280    -.0337121    .1161602
       trump |   .1426296   .0316286     4.51   0.000     .0804696    .2047897
       _cons |   .4954933   .0373704    13.26   0.000     .4220488    .5689378
------------------------------------------------------------------------------
(est3 stored)

. eststo  : reg cultl_thre2_v2 treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(10, 439)        =       5.31
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1050
                                                Root MSE          =     .27346

------------------------------------------------------------------------------
             |               Robust
cultl_t~2_v2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0134197   .0387938    -0.35   0.730    -.0896645     .062825
     treat23 |   -.014107   .0346394    -0.41   0.684    -.0821866    .0539726
     treat24 |   .0397666   .0372824     1.07   0.287    -.0335075    .1130407
        ageR |   .0710063   .0873783     0.81   0.417    -.1007255    .2427381
      female |   .0229615   .0279624     0.82   0.412    -.0319954    .0779183
     incomeR |  -.1135516   .0600944    -1.89   0.059    -.2316601    .0045568
       white |    .105537   .0478918     2.20   0.028     .0114113    .1996626
         rel |  -.0177096   .0077281    -2.29   0.022    -.0328983   -.0025209
       trump |   .1455552   .0312891     4.65   0.000     .0840601    .2070503
     college |  -.0440011   .0273319    -1.61   0.108    -.0977187    .0097165
       _cons |   .4672172   .0719532     6.49   0.000     .3258015    .6086328
------------------------------------------------------------------------------
(est4 stored)

. eststo  : reg econ_threa2 treat22 treat23 treat24 trump if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =      15.48
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0569
                                                Root MSE          =     .26269

------------------------------------------------------------------------------
             |               Robust
 econ_threa2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   -.011011   .0351133    -0.31   0.754    -.0800146    .0579927
     treat23 |  -.0212398   .0355276    -0.60   0.550    -.0910575    .0485779
     treat24 |  -.0010545   .0354996    -0.03   0.976    -.0708173    .0687082
       trump |   .3593393   .0469184     7.66   0.000     .2671367    .4515418
       _cons |   .3829118   .0260315    14.71   0.000     .3317555    .4340681
------------------------------------------------------------------------------
(est5 stored)

. eststo  : reg econ_threa2 treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(10, 451)        =       8.00
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0766
                                                Root MSE          =     .26167

------------------------------------------------------------------------------
             |               Robust
 econ_threa2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0126863   .0353166    -0.36   0.720    -.0820917    .0567192
     treat23 |  -.0182086   .0356609    -0.51   0.610    -.0882908    .0518736
     treat24 |  -.0059778    .036223    -0.17   0.869    -.0771645     .065209
        ageR |   .0385749   .0933072     0.41   0.679     -.144796    .2219458
      female |  -.0191292   .0249739    -0.77   0.444    -.0682089    .0299505
     incomeR |  -.0847674   .0598933    -1.42   0.158    -.2024719    .0329371
       white |  -.0004718   .0314378    -0.02   0.988    -.0622546    .0613111
         rel |   .0181352   .0097775     1.85   0.064    -.0010798    .0373503
       trump |   .3422558    .046203     7.41   0.000     .2514559    .4330557
     college |  -.0299781   .0258117    -1.16   0.246    -.0807042    .0207479
       _cons |   .4155684   .0474402     8.76   0.000     .3223372    .5087996
------------------------------------------------------------------------------
(est6 stored)

. eststo  : reg cultl_thre2_v2 treat22 treat23 treat24 trump if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =       3.42
                                                Prob > F          =     0.0091
                                                R-squared         =     0.0349
                                                Root MSE          =     .23299

------------------------------------------------------------------------------
             |               Robust
cultl_t~2_v2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0228293   .0301453     0.76   0.449    -.0364113    .0820698
     treat23 |  -.0193767   .0322508    -0.60   0.548    -.0827549    .0440015
     treat24 |   .0095885    .032604     0.29   0.769    -.0544838    .0736607
       trump |   .2400595   .0742825     3.23   0.001     .0940818    .3860372
       _cons |   .2416335   .0234397    10.31   0.000     .1955706    .2876964
------------------------------------------------------------------------------
(est7 stored)

. eststo  : reg cultl_thre2_v2 treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(10, 451)        =       2.44
                                                Prob > F          =     0.0076
                                                R-squared         =     0.0549
                                                Root MSE          =     .23209

------------------------------------------------------------------------------
             |               Robust
cultl_t~2_v2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0223283   .0304177     0.73   0.463    -.0374498    .0821064
     treat23 |  -.0167779   .0319936    -0.52   0.600     -.079653    .0460971
     treat24 |   .0090459   .0330439     0.27   0.784    -.0558932    .0739849
        ageR |   .0874019    .084469     1.03   0.301    -.0785998    .2534035
      female |   .0264334    .021819     1.21   0.226    -.0164462    .0693129
     incomeR |  -.0535703   .0524636    -1.02   0.308    -.1566737    .0495331
       white |  -.0101584    .026277    -0.39   0.699     -.061799    .0414822
         rel |   .0142772   .0082655     1.73   0.085    -.0019665     .030521
       trump |   .2244808   .0718551     3.12   0.002     .0832685    .3656931
     college |  -.0346527   .0223649    -1.55   0.122     -.078605    .0092997
       _cons |   .2435866   .0421283     5.78   0.000     .1607945    .3263787
------------------------------------------------------------------------------
(est8 stored)

. esttab using threat.tex, ar2 b(3) se(3) starlevels(* 0.1 ** .05 *** .01) label replace
(output written to threat.tex)

. eststo clear

. 
. 
. *** Generate Table D6 (Ingroup-Centric Beliefs by Party)
. eststo  : reg outgroupr treat22 treat23 treat24 trump if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =      10.29
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0864
                                                Root MSE          =     .26111

------------------------------------------------------------------------------
             |               Robust
   outgroupr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   -.101265    .035754    -2.83   0.005    -.1715326   -.0309973
     treat23 |  -.0384428   .0348311    -1.10   0.270    -.1068967     .030011
     treat24 |  -.0604278   .0345437    -1.75   0.081    -.1283169    .0074613
       trump |   .1642096   .0280496     5.85   0.000     .1090834    .2193359
       _cons |   .3297821   .0323224    10.20   0.000     .2662586    .3933056
------------------------------------------------------------------------------
(est1 stored)

. eststo  : reg outgroupr treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(10, 439)        =       6.59
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1244
                                                Root MSE          =     .25736

------------------------------------------------------------------------------
             |               Robust
   outgroupr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.1054987   .0350597    -3.01   0.003    -.1744043   -.0365931
     treat23 |  -.0412724   .0343515    -1.20   0.230    -.1087862    .0262415
     treat24 |  -.0700669   .0342691    -2.04   0.041    -.1374187   -.0027151
        ageR |  -.2184096   .0840185    -2.60   0.010    -.3835381   -.0532811
      female |  -.0106686   .0259678    -0.41   0.681    -.0617053    .0403681
     incomeR |  -.1449416   .0550358    -2.63   0.009     -.253108   -.0367752
       white |  -.0253143   .0414611    -0.61   0.542    -.1068012    .0561727
         rel |  -.0030226   .0070202    -0.43   0.667    -.0168199    .0107747
       trump |   .1673552   .0279909     5.98   0.000     .1123425    .2223679
     college |  -.0421656   .0253058    -1.67   0.096    -.0919012    .0075699
       _cons |   .5055034   .0620111     8.15   0.000     .3836278    .6273789
------------------------------------------------------------------------------
(est2 stored)

. eststo  : reg ingroupr treat22 treat23 treat24 trump if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =       8.29
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0640
                                                Root MSE          =     .31826

------------------------------------------------------------------------------
             |               Robust
    ingroupr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0863754   .0446556    -1.93   0.054    -.1741374    .0013866
     treat23 |  -.0632043   .0425479    -1.49   0.138    -.1468241    .0204155
     treat24 |  -.0174102    .042506    -0.41   0.682    -.1009477    .0661272
       trump |   .1692871   .0350926     4.82   0.000     .1003193    .2382548
       _cons |   .4774677   .0420311    11.36   0.000     .3948636    .5600719
------------------------------------------------------------------------------
(est3 stored)

. eststo  : reg ingroupr treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(10, 439)        =       4.51
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0802
                                                Root MSE          =     .31764

------------------------------------------------------------------------------
             |               Robust
    ingroupr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0861886   .0447708    -1.93   0.055    -.1741804    .0018031
     treat23 |  -.0662658   .0427404    -1.55   0.122     -.150267    .0177353
     treat24 |  -.0236645   .0431999    -0.55   0.584    -.1085688    .0612398
        ageR |  -.1274818   .1015947    -1.25   0.210    -.3271542    .0721906
      female |   -.015053   .0311399    -0.48   0.629    -.0762549    .0461489
     incomeR |   -.126871    .068309    -1.86   0.064    -.2611242    .0073823
       white |   .0315831   .0521182     0.61   0.545    -.0708491    .1340153
         rel |  -.0065385   .0089068    -0.73   0.463    -.0240437    .0109668
       trump |   .1712821    .034623     4.95   0.000     .1032347    .2393295
     college |  -.0275819   .0325003    -0.85   0.397    -.0914575    .0362936
       _cons |   .5689785    .079117     7.19   0.000     .4134833    .7244737
------------------------------------------------------------------------------
(est4 stored)

. eststo  : reg victimr treat22 treat23 treat24 trump if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =       9.50
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0754
                                                Root MSE          =     .29769

------------------------------------------------------------------------------
             |               Robust
     victimr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.1093217   .0410641    -2.66   0.008    -.1900253    -.028618
     treat23 |  -.0294516   .0374875    -0.79   0.432     -.103126    .0442229
     treat24 |  -.0161874   .0396273    -0.41   0.683    -.0940673    .0616925
       trump |    .172735   .0330303     5.23   0.000     .1078203    .2376497
       _cons |   .5526517   .0387066    14.28   0.000     .4765814    .6287221
------------------------------------------------------------------------------
(est5 stored)

. eststo  : reg victimr treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(10, 439)        =       5.51
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1030
                                                Root MSE          =     .29521

------------------------------------------------------------------------------
             |               Robust
     victimr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0987878   .0408048    -2.42   0.016    -.1789848   -.0185908
     treat23 |  -.0281579   .0364894    -0.77   0.441    -.0998735    .0435577
     treat24 |  -.0173876   .0393936    -0.44   0.659     -.094811    .0600359
        ageR |    .046357    .097712     0.47   0.635    -.1456844    .2383984
      female |   .0150458   .0288183     0.52   0.602    -.0415932    .0716847
     incomeR |  -.1586459    .061934    -2.56   0.011      -.28037   -.0369219
       white |   .0969021   .0570521     1.70   0.090    -.0152272    .2090313
         rel |  -.0121279   .0081255    -1.49   0.136    -.0280977    .0038419
       trump |   .1787495   .0325338     5.49   0.000     .1148082    .2426908
     college |   .0114568   .0294258     0.39   0.697    -.0463763    .0692898
       _cons |   .5196056    .076288     6.81   0.000     .3696705    .6695408
------------------------------------------------------------------------------
(est6 stored)

. eststo  : reg outgroupr treat22 treat23 treat24 trump if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =       2.28
                                                Prob > F          =     0.0603
                                                R-squared         =     0.0186
                                                Root MSE          =     .20465

------------------------------------------------------------------------------
             |               Robust
   outgroupr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0348669   .0279134    -1.25   0.212    -.0897215    .0199877
     treat23 |  -.0593051   .0281266    -2.11   0.036    -.1145785   -.0040316
     treat24 |   -.026927   .0300019    -0.90   0.370    -.0858858    .0320319
       trump |    .109176   .0469209     2.33   0.020     .0169686    .2013834
       _cons |   .1808724    .022206     8.15   0.000     .1372339    .2245109
------------------------------------------------------------------------------
(est7 stored)

. eststo  : reg outgroupr treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(10, 451)        =       3.11
                                                Prob > F          =     0.0008
                                                R-squared         =     0.0822
                                                Root MSE          =     .19921

------------------------------------------------------------------------------
             |               Robust
   outgroupr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0323073   .0276957    -1.17   0.244     -.086736    .0221214
     treat23 |  -.0480831   .0283279    -1.70   0.090    -.1037541    .0075879
     treat24 |  -.0251931   .0301144    -0.84   0.403    -.0843752    .0339889
        ageR |  -.1413935   .0668352    -2.12   0.035    -.2727406   -.0100463
      female |   .0233227   .0188626     1.24   0.217    -.0137468    .0603922
     incomeR |  -.0507827   .0448831    -1.13   0.258    -.1389886    .0374232
       white |   .0068659   .0232412     0.30   0.768    -.0388086    .0525403
         rel |   .0376749   .0094676     3.98   0.000     .0190687     .056281
       trump |   .0940412   .0484577     1.94   0.053    -.0011898    .1892722
     college |   -.014435   .0190083    -0.76   0.448    -.0517908    .0229209
       _cons |   .1912357   .0380232     5.03   0.000     .1165112    .2659603
------------------------------------------------------------------------------
(est8 stored)

. eststo  : reg ingroupr treat22 treat23 treat24 trump if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =       3.79
                                                Prob > F          =     0.0048
                                                R-squared         =     0.0323
                                                Root MSE          =     .28235

------------------------------------------------------------------------------
             |               Robust
    ingroupr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0557264   .0387419    -1.44   0.151    -.1318607    .0204079
     treat23 |  -.0820027   .0391622    -2.09   0.037    -.1589631   -.0050423
     treat24 |   -.050335   .0397867    -1.27   0.206    -.1285224    .0278525
       trump |   .2435815     .07572     3.22   0.001     .0947789    .3923841
       _cons |   .2871313   .0302091     9.50   0.000     .2277653    .3464974
------------------------------------------------------------------------------
(est9 stored)

. eststo  : reg ingroupr treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(10, 451)        =       2.73
                                                Prob > F          =     0.0029
                                                R-squared         =     0.0642
                                                Root MSE          =     .27949

------------------------------------------------------------------------------
             |               Robust
    ingroupr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0600817   .0390187    -1.54   0.124    -.1367628    .0165993
     treat23 |  -.0780462   .0391825    -1.99   0.047    -.1550492   -.0010433
     treat24 |  -.0515714   .0400267    -1.29   0.198    -.1302334    .0270906
        ageR |   .1082282   .1013834     1.07   0.286    -.0910143    .3074708
      female |    .041852   .0272888     1.53   0.126     -.011777    .0954809
     incomeR |   .0589246   .0641332     0.92   0.359    -.0671124    .1849616
       white |   -.037987   .0333878    -1.14   0.256     -.103602    .0276279
         rel |   .0294675   .0116392     2.53   0.012     .0065937    .0523413
       trump |   .2269442    .076185     2.98   0.003     .0772225    .3766659
     college |  -.0181652   .0276217    -0.66   0.511    -.0724485    .0361181
       _cons |   .2397992   .0499289     4.80   0.000     .1416771    .3379214
------------------------------------------------------------------------------
(est10 stored)

. eststo  : reg victimr treat22 treat23 treat24 trump if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(4, 457)         =       9.36
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0724
                                                Root MSE          =     .27845

------------------------------------------------------------------------------
             |               Robust
     victimr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0542397   .0372951    -1.45   0.147    -.1275309    .0190516
     treat23 |  -.0896422   .0375822    -2.39   0.017    -.1634976   -.0157868
     treat24 |  -.0564396   .0386123    -1.46   0.145    -.1323193    .0194402
       trump |   .4063051   .0712837     5.70   0.000     .2662205    .5463896
       _cons |   .3076832   .0280765    10.96   0.000     .2525082    .3628582
------------------------------------------------------------------------------
(est11 stored)

. eststo  : reg victimr treat22 treat23 treat24 ageR female incomeR white rel trump college if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(10, 451)        =       5.48
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0993
                                                Root MSE          =      .2762

------------------------------------------------------------------------------
             |               Robust
     victimr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0546133   .0378681    -1.44   0.150    -.1290332    .0198066
     treat23 |  -.0836542   .0373955    -2.24   0.026    -.1571453   -.0101631
     treat24 |  -.0584851   .0387079    -1.51   0.132    -.1345553    .0175851
        ageR |    .011986   .0999821     0.12   0.905    -.1845026    .2084746
      female |   .0253695   .0266394     0.95   0.341    -.0269832    .0777222
     incomeR |  -.0278019   .0604791    -0.46   0.646    -.1466577    .0910539
       white |  -.0378478   .0321798    -1.18   0.240    -.1010889    .0253932
         rel |    .028766   .0105109     2.74   0.006     .0081096    .0494224
       trump |   .3932147   .0705508     5.57   0.000     .2545655    .5318638
     college |  -.0369722   .0272503    -1.36   0.176    -.0905255    .0165812
       _cons |   .3294288   .0513736     6.41   0.000     .2284674    .4303902
------------------------------------------------------------------------------
(est12 stored)

. esttab using gic.tex, ar2 b(3) se(3) starlevels(* 0.1 ** .05 *** .01) label replace
(output written to gic.tex)

. eststo clear

. 
. 
. *** Generate Table D7 (Potential Mediators) 
. eststo  : reg immig_index treat22 treat23 treat24 trump if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =      20.78
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1739
                                                Root MSE          =     .22588

------------------------------------------------------------------------------
             |               Robust
 immig_index |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0723285   .0294754     2.45   0.015     .0144003    .1302566
     treat23 |   .0285185   .0303451     0.94   0.348    -.0311189    .0881559
     treat24 |   .0139463   .0296187     0.47   0.638    -.0442637    .0721563
       trump |   -.228239   .0269447    -8.47   0.000    -.2811936   -.1752844
       _cons |   .4792298   .0313787    15.27   0.000     .4175609    .5408987
------------------------------------------------------------------------------
(est1 stored)

. eststo  : reg outgroupr treat22 treat23 treat24 trump if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =      10.29
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0864
                                                Root MSE          =     .26111

------------------------------------------------------------------------------
             |               Robust
   outgroupr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   -.101265    .035754    -2.83   0.005    -.1715326   -.0309973
     treat23 |  -.0384428   .0348311    -1.10   0.270    -.1068967     .030011
     treat24 |  -.0604278   .0345437    -1.75   0.081    -.1283169    .0074613
       trump |   .1642096   .0280496     5.85   0.000     .1090834    .2193359
       _cons |   .3297821   .0323224    10.20   0.000     .2662586    .3933056
------------------------------------------------------------------------------
(est2 stored)

. eststo  : reg immig_index treat22 treat23 treat24 trump outgroupr if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(5, 444)         =      38.07
                                                Prob > F          =     0.0000
                                                R-squared         =     0.3016
                                                Root MSE          =     .20792

------------------------------------------------------------------------------
             |               Robust
 immig_index |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0378808   .0272717     1.39   0.166    -.0157167    .0914784
     treat23 |   .0154413   .0278632     0.55   0.580    -.0393189    .0702014
     treat24 |  -.0066096   .0270806    -0.24   0.807    -.0598318    .0466125
       trump |  -.1723792    .025051    -6.88   0.000    -.2216125   -.1231459
   outgroupr |  -.3401734   .0393175    -8.65   0.000    -.4174448   -.2629019
       _cons |   .5914129   .0306181    19.32   0.000     .5312385    .6515873
------------------------------------------------------------------------------
(est3 stored)

. eststo  : reg ingroupr treat22 treat23 treat24 trump if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =       8.29
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0640
                                                Root MSE          =     .31826

------------------------------------------------------------------------------
             |               Robust
    ingroupr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0863754   .0446556    -1.93   0.054    -.1741374    .0013866
     treat23 |  -.0632043   .0425479    -1.49   0.138    -.1468241    .0204155
     treat24 |  -.0174102    .042506    -0.41   0.682    -.1009477    .0661272
       trump |   .1692871   .0350926     4.82   0.000     .1003193    .2382548
       _cons |   .4774677   .0420311    11.36   0.000     .3948636    .5600719
------------------------------------------------------------------------------
(est4 stored)

. eststo  : reg immig_index treat22 treat23 treat24 trump ingroupr if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(5, 444)         =      54.21
                                                Prob > F          =     0.0000
                                                R-squared         =     0.3444
                                                Root MSE          =     .20146

------------------------------------------------------------------------------
             |               Robust
 immig_index |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0444778   .0264754     1.68   0.094     -.007555    .0965106
     treat23 |   .0081391   .0276144     0.29   0.768    -.0461321    .0624103
     treat24 |   .0083326   .0261101     0.32   0.750    -.0429821    .0596472
       trump |  -.1736545   .0256517    -6.77   0.000    -.2240684   -.1232407
    ingroupr |  -.3224373   .0304144   -10.60   0.000    -.3822114   -.2626632
       _cons |   .6331832   .0295854    21.40   0.000     .5750383    .6913281
------------------------------------------------------------------------------
(est5 stored)

. eststo  : reg victimr treat22 treat23 treat24 trump if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =       9.50
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0754
                                                Root MSE          =     .29769

------------------------------------------------------------------------------
             |               Robust
     victimr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.1093217   .0410641    -2.66   0.008    -.1900253    -.028618
     treat23 |  -.0294516   .0374875    -0.79   0.432     -.103126    .0442229
     treat24 |  -.0161874   .0396273    -0.41   0.683    -.0940673    .0616925
       trump |    .172735   .0330303     5.23   0.000     .1078203    .2376497
       _cons |   .5526517   .0387066    14.28   0.000     .4765814    .6287221
------------------------------------------------------------------------------
(est6 stored)

. eststo  : reg immig_index treat22 treat23 treat24 trump victimr if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(5, 444)         =      62.42
                                                Prob > F          =     0.0000
                                                R-squared         =     0.4169
                                                Root MSE          =     .18999

------------------------------------------------------------------------------
             |               Robust
 immig_index |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0273396    .025475     1.07   0.284    -.0227268    .0774061
     treat23 |   .0163984   .0246909     0.66   0.507    -.0321272     .064924
     treat24 |   .0072847   .0240136     0.30   0.762    -.0399097    .0544792
       trump |  -.1571539    .023706    -6.63   0.000    -.2037437    -.110564
     victimr |   -.411527    .033105   -12.43   0.000    -.4765889   -.3464651
       _cons |   .7066609   .0287121    24.61   0.000     .6502324    .7630894
------------------------------------------------------------------------------
(est7 stored)

. eststo  : reg econ_threa2 treat22 treat23 treat24 trump if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =       8.52
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0733
                                                Root MSE          =     .23582

------------------------------------------------------------------------------
             |               Robust
 econ_threa2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0724354   .0312333    -2.32   0.021    -.1338185   -.0110522
     treat23 |  -.0668986   .0299517    -2.23   0.026     -.125763   -.0080341
     treat24 |  -.0170711   .0299205    -0.57   0.569    -.0758741    .0417318
       trump |   .1287081   .0266099     4.84   0.000     .0764113    .1810048
       _cons |   .6839295    .028962    23.61   0.000     .6270102    .7408488
------------------------------------------------------------------------------
(est8 stored)

. eststo  : reg immig_index treat22 treat23 treat24 trump econ_threa2 if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(5, 444)         =      58.34
                                                Prob > F          =     0.0000
                                                R-squared         =     0.3801
                                                Root MSE          =     .19589

------------------------------------------------------------------------------
             |               Robust
 immig_index |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0376626   .0260224     1.45   0.149    -.0134799     .088805
     treat23 |  -.0034976   .0269219    -0.13   0.897    -.0564078    .0494126
     treat24 |   .0057764   .0260452     0.22   0.825    -.0454108    .0569636
       trump |  -.1666423   .0249503    -6.68   0.000    -.2156776   -.1176069
 econ_threa2 |  -.4785769   .0423956   -11.29   0.000    -.5618979   -.3952558
       _cons |   .8065426   .0380528    21.20   0.000     .7317567    .8813286
------------------------------------------------------------------------------
(est9 stored)

. esttab using mediation_rep.tex, ar2 b(3) se(3) starlevels(* 0.1 ** .05 *** .01) label replace
(output written to mediation_rep.tex)

. eststo clear

. 
. 
. *** Mediation Checks (mentioned in text) 
. gen outgroupr2 = outgroupr if rep == 1
(537 missing values generated)

. gen ingroupr2 = ingroupr if rep == 1
(537 missing values generated)

. gen victimr2 = victimr if rep == 1
(537 missing values generated)

. gen econ_threa22 = econ_threa2 if rep == 1
(537 missing values generated)

. medeff (regress outgroupr2 treat22 treat23 treat24 trump) (regress immig_index treat22 treat23 treat24 outgroupr2 trump), mediate(outgroupr2) treat(treat22) 
> sims(1000) seed(1)
Using 0 and 1 as treatment values

      Source |       SS           df       MS      Number of obs   =       450
-------------+----------------------------------   F(4, 445)       =     10.52
       Model |  2.86773382         4  .716933454   Prob > F        =    0.0000
    Residual |  30.3394262       445  .068178486   R-squared       =    0.0864
-------------+----------------------------------   Adj R-squared   =    0.0781
       Total |  33.2071601       449   .07395804   Root MSE        =    .26111

------------------------------------------------------------------------------
  outgroupr2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   -.101265   .0349479    -2.90   0.004    -.1699484   -.0325815
     treat23 |  -.0384428   .0345054    -1.11   0.266    -.1062566    .0293709
     treat24 |  -.0604278   .0340338    -1.78   0.076    -.1273148    .0064591
       trump |   .1642096   .0283044     5.80   0.000     .1085828    .2198364
       _cons |   .3297821   .0323205    10.20   0.000     .2662624    .3933019
------------------------------------------------------------------------------

      Source |       SS           df       MS      Number of obs   =       450
-------------+----------------------------------   F(5, 444)       =     38.35
       Model |  8.29026184         5  1.65805237   Prob > F        =    0.0000
    Residual |  19.1948146       444  .043231564   R-squared       =    0.3016
-------------+----------------------------------   Adj R-squared   =    0.2938
       Total |  27.4850765       449  .061213979   Root MSE        =    .20792

------------------------------------------------------------------------------
 immig_index |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0378808   .0280903     1.35   0.178    -.0173257    .0930874
  outgroupr2 |  -.3401734   .0377482    -9.01   0.000    -.4143608   -.2659859
     treat23 |   .0154413   .0275149     0.56   0.575    -.0386344     .069517
     treat24 |  -.0066096   .0271969    -0.24   0.808    -.0600604    .0468411
       trump |  -.1723792   .0233756    -7.37   0.000    -.2183198   -.1264387
       _cons |   .5914129   .0285894    20.69   0.000     .5352256    .6476002
------------------------------------------------------------------------------
The number of observations in the data is less than the number of simulations. Expanding the data to the number of simulations
------------------------------------------------------------------------------------
        Effect                 |  Mean           [95% Conf. Interval]
-------------------------------+----------------------------------------------------
        ACME                   |  .0343234      .0089127       .059741
        Direct Effect          |  .0388195     -.0140095      .0927466
        Total Effect           |  .0731429      .0137193      .1330333
        % of Tot Eff mediated  |  .4673564      .2508852      2.008797
------------------------------------------------------------------------------------

. medeff (regress ingroupr2  treat22 treat23 treat24 trump) (regress immig_index treat22 treat23 treat24 ingroupr2 trump), mediate(ingroupr2) treat(treat22) si
> ms(1000) seed(1)
Using 0 and 1 as treatment values

      Source |       SS           df       MS      Number of obs   =       450
-------------+----------------------------------   F(4, 445)       =      7.60
       Model |  3.07971516         4   .76992879   Prob > F        =    0.0000
    Residual |  45.0739259       445  .101289721   R-squared       =    0.0640
-------------+----------------------------------   Adj R-squared   =    0.0555
       Total |  48.1536411       449  .107246417   Root MSE        =    .31826

------------------------------------------------------------------------------
   ingroupr2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0863754   .0425971    -2.03   0.043     -.170092   -.0026589
     treat23 |  -.0632043   .0420578    -1.50   0.134    -.1458608    .0194522
     treat24 |  -.0174102   .0414829    -0.42   0.675     -.098937    .0641166
       trump |   .1692871   .0344995     4.91   0.000     .1014849    .2370892
       _cons |   .4774677   .0393946    12.12   0.000     .4000451    .5548903
------------------------------------------------------------------------------

      Source |       SS           df       MS      Number of obs   =       450
-------------+----------------------------------   F(5, 444)       =     46.65
       Model |  9.46559346         5  1.89311869   Prob > F        =    0.0000
    Residual |   18.019483       444  .040584421   R-squared       =    0.3444
-------------+----------------------------------   Adj R-squared   =    0.3370
       Total |  27.4850765       449  .061213979   Root MSE        =    .20146

------------------------------------------------------------------------------
 immig_index |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0444778   .0270878     1.64   0.101    -.0087585    .0977141
   ingroupr2 |  -.3224373   .0300066   -10.75   0.000    -.3814099   -.2634647
     treat23 |   .0081391   .0266896     0.30   0.761    -.0443146    .0605927
     treat24 |   .0083326   .0262635     0.32   0.751    -.0432836    .0599488
       trump |  -.1736545   .0224208    -7.75   0.000    -.2177187   -.1295904
       _cons |   .6331832   .0287592    22.02   0.000     .5766621    .6897043
------------------------------------------------------------------------------
The number of observations in the data is less than the number of simulations. Expanding the data to the number of simulations
------------------------------------------------------------------------------------
        Effect                 |  Mean           [95% Conf. Interval]
-------------------------------+----------------------------------------------------
        ACME                   |  .0277362     -.0008555      .0557684
        Direct Effect          |   .045383     -.0055607      .0973855
        Total Effect           |  .0731192       .013852      .1315278
        % of Tot Eff mediated  |  .3777233      .2043019      1.607492
------------------------------------------------------------------------------------

. medeff (regress victimr2  treat22 treat23 treat24 trump) (regress immig_index treat22 treat23 treat24 victimr2 trump), mediate(victimr2) treat(treat22) sims(
> 1000) seed(1)
Using 0 and 1 as treatment values

      Source |       SS           df       MS      Number of obs   =       450
-------------+----------------------------------   F(4, 445)       =      9.07
       Model |  3.21576304         4  .803940759   Prob > F        =    0.0000
    Residual |   39.435841       445  .088619867   R-squared       =    0.0754
-------------+----------------------------------   Adj R-squared   =    0.0671
       Total |  42.6516041       449  .094992437   Root MSE        =    .29769

------------------------------------------------------------------------------
    victimr2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.1093217    .039844    -2.74   0.006    -.1876275   -.0310158
     treat23 |  -.0294516   .0393395    -0.75   0.454    -.1067659    .0478627
     treat24 |  -.0161874   .0388018    -0.42   0.677    -.0924451    .0600702
       trump |    .172735   .0322697     5.35   0.000      .109315    .2361549
       _cons |   .5526517   .0368485    15.00   0.000      .480233    .6250704
------------------------------------------------------------------------------

      Source |       SS           df       MS      Number of obs   =       450
-------------+----------------------------------   F(5, 444)       =     63.49
       Model |  11.4580824         5  2.29161649   Prob > F        =    0.0000
    Residual |   16.026994       444  .036096833   R-squared       =    0.4169
-------------+----------------------------------   Adj R-squared   =    0.4103
       Total |  27.4850765       449  .061213979   Root MSE        =    .18999

------------------------------------------------------------------------------
 immig_index |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0273396   .0256434     1.07   0.287    -.0230578    .0777371
    victimr2 |   -.411527   .0302544   -13.60   0.000    -.4709867   -.3520673
     treat23 |   .0163984    .025123     0.65   0.514    -.0329764    .0657731
     treat24 |   .0072847   .0247689     0.29   0.769    -.0413941    .0559635
       trump |  -.1571539   .0212478    -7.40   0.000    -.1989126   -.1153951
       _cons |   .7066609   .0288553    24.49   0.000     .6499509    .7633709
------------------------------------------------------------------------------
The number of observations in the data is less than the number of simulations. Expanding the data to the number of simulations
------------------------------------------------------------------------------------
        Effect                 |  Mean           [95% Conf. Interval]
-------------------------------+----------------------------------------------------
        ACME                   |  .0448475      .0102567      .0778914
        Direct Effect          |  .0281966     -.0200305       .077426
        Total Effect           |  .0730441      .0120507      .1322564
        % of Tot Eff mediated  |  .6047918      .3322539        2.5233
------------------------------------------------------------------------------------

. medeff (regress econ_threa22 treat22 treat23 treat24 trump) (regress immig_index treat22 treat23 treat24 econ_threa22 trump), mediate(econ_threa22) treat(tre
> at22) sims(1000) seed(1)
Using 0 and 1 as treatment values

      Source |       SS           df       MS      Number of obs   =       450
-------------+----------------------------------   F(4, 445)       =      8.80
       Model |  1.95755103         4  .489387758   Prob > F        =    0.0000
    Residual |  24.7459049       445  .055608775   R-squared       =    0.0733
-------------+----------------------------------   Adj R-squared   =    0.0650
       Total |  26.7034559       449  .059473176   Root MSE        =    .23582

------------------------------------------------------------------------------
econ_threa22 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.0724354   .0315623    -2.29   0.022    -.1344651   -.0104056
     treat23 |  -.0668986   .0311627    -2.15   0.032    -.1281429   -.0056542
     treat24 |  -.0170711   .0307368    -0.56   0.579    -.0774784    .0433362
       trump |   .1287081   .0255624     5.04   0.000     .0784701     .178946
       _cons |   .6839295   .0291894    23.43   0.000     .6265632    .7412958
------------------------------------------------------------------------------

      Source |       SS           df       MS      Number of obs   =       450
-------------+----------------------------------   F(5, 444)       =     54.45
       Model |  10.4471451         5  2.08942901   Prob > F        =    0.0000
    Residual |  17.0379314       444  .038373719   R-squared       =    0.3801
-------------+----------------------------------   Adj R-squared   =    0.3731
       Total |  27.4850765       449  .061213979   Root MSE        =    .19589

------------------------------------------------------------------------------
 immig_index |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .0376626   .0263736     1.43   0.154      -.01417    .0894952
econ_threa22 |  -.4785769   .0393791   -12.15   0.000    -.5559694   -.4011844
     treat23 |  -.0034976   .0260206    -0.13   0.893    -.0546365    .0476413
     treat24 |   .0057764    .025542     0.23   0.821    -.0444217    .0559746
       trump |  -.1666423   .0218312    -7.63   0.000    -.2095476   -.1237369
       _cons |   .8065426   .0362396    22.26   0.000     .7353201    .8777652
------------------------------------------------------------------------------
The number of observations in the data is less than the number of simulations. Expanding the data to the number of simulations
------------------------------------------------------------------------------------
        Effect                 |  Mean           [95% Conf. Interval]
-------------------------------+----------------------------------------------------
        ACME                   |  .0345396      .0025523      .0650562
        Direct Effect          |  .0385439     -.0110565      .0891753
        Total Effect           |  .0730835      .0122911      .1315593
        % of Tot Eff mediated  |  .4688454      .2530128      1.963034
------------------------------------------------------------------------------------

. 
. 
. *** Generate Table D8 (Victim/Asylum Seekers)
. set more off

. eststo  : reg percent_1 treat22 treat23 treat24 trump if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =       3.48
                                                Prob > F          =     0.0082
                                                R-squared         =     0.0412
                                                Root MSE          =     19.187

------------------------------------------------------------------------------
             |               Robust
   percent_1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |    1.42083   2.598421     0.55   0.585     -3.68587     6.52753
     treat23 |   -.895423   2.454514    -0.36   0.715    -5.719302    3.928456
     treat24 |   .1186896   2.513418     0.05   0.962    -4.820954    5.058334
       trump |  -9.050283   2.443841    -3.70   0.000    -13.85319   -4.247381
       _cons |   29.26047   2.683889    10.90   0.000      23.9858    34.53514
------------------------------------------------------------------------------
(est1 stored)

. eststo  : reg percent_1 treat22 treat23 treat24 trump female incomeR white rel college if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(9, 440)         =       4.98
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0881
                                                Root MSE          =     18.819

------------------------------------------------------------------------------
             |               Robust
   percent_1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |    .642728   2.563534     0.25   0.802    -4.395565    5.681021
     treat23 |  -1.668435   2.429393    -0.69   0.493    -6.443091     3.10622
     treat24 |  -.7472924   2.492912    -0.30   0.764    -5.646788    4.152203
       trump |  -10.22726   2.443864    -4.18   0.000    -15.03036   -5.424163
      female |  -5.201032   1.916913    -2.71   0.007    -8.968475   -1.433589
     incomeR |  -.6868765   3.555402    -0.19   0.847    -7.674557    6.300804
       white |  -3.935509   3.721863    -1.06   0.291    -11.25035     3.37933
         rel |    1.57849   .5288519     2.98   0.003     .5391001    2.617879
     college |  -.2919306   1.853265    -0.16   0.875    -3.934282    3.350421
       _cons |   33.77802   4.930059     6.85   0.000     24.08862    43.46741
------------------------------------------------------------------------------
(est2 stored)

. eststo  : reg percent_2 treat22 treat23 treat24 trump if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(4, 445)         =       1.22
                                                Prob > F          =     0.2995
                                                R-squared         =     0.0106
                                                Root MSE          =     20.912

------------------------------------------------------------------------------
             |               Robust
   percent_2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   1.327595   2.890125     0.46   0.646    -4.352393    7.007584
     treat23 |   3.788135   2.817506     1.34   0.179    -1.749136    9.325406
     treat24 |  -.5077433   2.672675    -0.19   0.849    -5.760377     4.74489
       trump |  -2.714251   2.498801    -1.09   0.278    -7.625169    2.196666
       _cons |   26.12175   2.871425     9.10   0.000     20.47851    31.76499
------------------------------------------------------------------------------
(est3 stored)

. eststo  : reg percent_2 treat22 treat23 treat24 trump female incomeR white rel college if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(9, 440)         =       4.35
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0661
                                                Root MSE          =     20.432

------------------------------------------------------------------------------
             |               Robust
   percent_2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   .4980885   2.812272     0.18   0.860    -5.029066    6.025243
     treat23 |   2.770852   2.757768     1.00   0.316    -2.649182    8.190886
     treat24 |  -1.676157   2.670065    -0.63   0.530    -6.923824    3.571509
       trump |  -4.003091   2.436528    -1.64   0.101     -8.79177    .7855888
      female |  -7.244552   1.999273    -3.62   0.000    -11.17386    -3.31524
     incomeR |  -5.706909   4.245079    -1.34   0.180    -14.05006    2.636243
       white |  -3.305163   3.251185    -1.02   0.310    -9.694945    3.084618
         rel |   1.445149   .5851301     2.47   0.014     .2951521    2.595147
     college |  -.0367878   1.999707    -0.02   0.985    -3.966953    3.893377
       _cons |   33.31445   4.669222     7.13   0.000      24.1377     42.4912
------------------------------------------------------------------------------
(est4 stored)

. eststo  : reg percent_1 treat22 treat23 treat24 trump if rep == 0, robust

Linear regression                               Number of obs     =        460
                                                F(4, 455)         =       2.50
                                                Prob > F          =     0.0419
                                                R-squared         =     0.0141
                                                Root MSE          =     22.658

------------------------------------------------------------------------------
             |               Robust
   percent_1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   3.147891   3.031351     1.04   0.300    -2.809294    9.105077
     treat23 |   3.922069   2.970255     1.32   0.187    -1.915051    9.759188
     treat24 |   4.393743     3.0611     1.44   0.152    -1.621904    10.40939
       trump |  -12.32353   4.537336    -2.72   0.007    -21.24026   -3.406799
       _cons |   29.26387   2.187752    13.38   0.000     24.96452    33.56322
------------------------------------------------------------------------------
(est5 stored)

. eststo  : reg percent_1 treat22 treat23 treat24 trump female incomeR white rel college if rep == 0, robust

Linear regression                               Number of obs     =        460
                                                F(9, 450)         =       2.38
                                                Prob > F          =     0.0122
                                                R-squared         =     0.0355
                                                Root MSE          =     22.535

------------------------------------------------------------------------------
             |               Robust
   percent_1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |   3.121093   3.079461     1.01   0.311    -2.930817    9.173002
     treat23 |    3.87153   2.956331     1.31   0.191    -1.938399    9.681458
     treat24 |   3.742317   3.152405     1.19   0.236    -2.452945    9.937579
       trump |  -12.62624   4.325629    -2.92   0.004    -21.12718   -4.125299
      female |  -4.794235   2.183925    -2.20   0.029    -9.086193   -.5022767
     incomeR |  -8.586399    4.98115    -1.72   0.085     -18.3756    1.202805
       white |  -.5835981   2.575676    -0.23   0.821    -5.645444    4.478248
         rel |   .2516532    .857787     0.29   0.769    -1.434112    1.937419
     college |  -1.685129   2.218931    -0.76   0.448    -6.045882    2.675624
       _cons |   35.71794   3.811831     9.37   0.000     28.22674    43.20914
------------------------------------------------------------------------------
(est6 stored)

. eststo  : reg percent_2 treat22 treat23 treat24 trump if rep == 0, robust

Linear regression                               Number of obs     =        460
                                                F(4, 455)         =       0.54
                                                Prob > F          =     0.7075
                                                R-squared         =     0.0046
                                                Root MSE          =     23.101

------------------------------------------------------------------------------
             |               Robust
   percent_2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.4986609   2.970368    -0.17   0.867    -6.336002     5.33868
     treat23 |   1.763995   3.020395     0.58   0.559    -4.171659    7.699649
     treat24 |   3.452299   2.974654     1.16   0.246    -2.393466    9.298064
       trump |  -1.454086     6.8376    -0.21   0.832    -14.89128    11.98311
       _cons |   26.76757   2.056354    13.02   0.000     22.72644     30.8087
------------------------------------------------------------------------------
(est7 stored)

. eststo  : reg percent_2 treat22 treat23 treat24 trump female incomeR white rel college if rep == 0, robust

Linear regression                               Number of obs     =        460
                                                F(9, 450)         =       2.36
                                                Prob > F          =     0.0129
                                                R-squared         =     0.0388
                                                Root MSE          =     22.826

------------------------------------------------------------------------------
             |               Robust
   percent_2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     treat22 |  -.4940048     2.9793    -0.17   0.868    -6.349073    5.361064
     treat23 |   1.601868   2.950015     0.54   0.587    -4.195647    7.399384
     treat24 |   2.553915   3.003533     0.85   0.396    -3.348777    8.456607
       trump |  -1.269476   6.625939    -0.19   0.848     -14.2911    11.75215
      female |  -6.102443    2.20295    -2.77   0.006    -10.43179   -1.773095
     incomeR |  -10.35685   4.877665    -2.12   0.034    -19.94268   -.7710258
       white |  -2.548887   2.638461    -0.97   0.335    -7.734121    2.636347
         rel |   .0263569    .825217     0.03   0.975    -1.595401    1.648114
     college |  -2.337203   2.266109    -1.03   0.303    -6.790673    2.116267
       _cons |   36.51367   3.613024    10.11   0.000     29.41317    43.61416
------------------------------------------------------------------------------
(est8 stored)

. esttab using victimcount.tex, ar2 b(3) se(3) starlevels(* 0.1 ** .05 *** .01) label replace
(output written to victimcount.tex)

. eststo clear

. 
. 
. *** Generate Table D9 (Support for Immigration by Education)
. gen treat22_college = treat22*college

. gen treat23_college = treat23*college

. gen treat24_college = treat24*college

. 
. set more off

. eststo  : reg immig_index treat22 treat23 treat24 college treat22_college treat23_college treat24_college trump if rep == 1, robust

Linear regression                               Number of obs     =        450
                                                F(8, 441)         =      11.01
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1844
                                                Root MSE          =     .22546

---------------------------------------------------------------------------------
                |               Robust
    immig_index |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        treat22 |   .0301033   .0400505     0.75   0.453    -.0486103    .1088169
        treat23 |   .0480398   .0420582     1.14   0.254    -.0346196    .1306992
        treat24 |   .0281841    .041891     0.67   0.501    -.0541467    .1105148
        college |  -.0000455   .0404722    -0.00   0.999    -.0795878    .0794968
treat22_college |   .0924724   .0589568     1.57   0.117    -.0233988    .2083436
treat23_college |  -.0391149   .0597819    -0.65   0.513    -.1566078     .078378
treat24_college |  -.0317442   .0593902    -0.53   0.593    -.1484672    .0849787
          trump |  -.2272841   .0271801    -8.36   0.000    -.2807027   -.1738654
          _cons |   .4785101   .0380631    12.57   0.000     .4037024    .5533178
---------------------------------------------------------------------------------
(est1 stored)

. eststo  : reg immig_index treat22 treat23 treat24 college treat22_college treat23_college treat24_college trump female incomeR white rel college if rep == 1,
>  robust
note: college omitted because of collinearity

Linear regression                               Number of obs     =        450
                                                F(12, 437)        =       9.42
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2080
                                                Root MSE          =     .22319

---------------------------------------------------------------------------------
                |               Robust
    immig_index |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        treat22 |   .0161602   .0401378     0.40   0.687    -.0627269    .0950473
        treat23 |   .0397624   .0423401     0.94   0.348    -.0434533     .122978
        treat24 |   .0195739   .0416389     0.47   0.639    -.0622635    .1014113
        college |  -.0274981   .0403514    -0.68   0.496     -.106805    .0518087
treat22_college |   .1065886    .058759     1.81   0.070    -.0088968     .222074
treat23_college |  -.0294588   .0591648    -0.50   0.619    -.1457417    .0868242
treat24_college |  -.0234095   .0581508    -0.40   0.687    -.1376995    .0908804
          trump |  -.2373515   .0269384    -8.81   0.000    -.2902965   -.1844065
         female |  -.0098467   .0225363    -0.44   0.662    -.0541396    .0344463
        incomeR |   .0714534   .0476667     1.50   0.135    -.0222311    .1651378
          white |  -.0497044   .0371045    -1.34   0.181    -.1226298     .023221
            rel |   .0174342   .0063576     2.74   0.006      .004939    .0299295
        college |          0  (omitted)
          _cons |   .4890992   .0548361     8.92   0.000     .3813238    .5968746
---------------------------------------------------------------------------------
(est2 stored)

. eststo  : reg immig_index treat22 treat23 treat24 college treat22_college treat23_college treat24_college trump if rep == 0, robust

Linear regression                               Number of obs     =        462
                                                F(8, 453)         =       7.79
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1180
                                                Root MSE          =     .19799

---------------------------------------------------------------------------------
                |               Robust
    immig_index |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        treat22 |   .0380641    .037172     1.02   0.306    -.0349868     .111115
        treat23 |   .0457117   .0432474     1.06   0.291    -.0392786     .130702
        treat24 |   .0204636   .0415522     0.49   0.623    -.0611953    .1021226
        college |   .0316579   .0369825     0.86   0.392    -.0410206    .1043363
treat22_college |  -.0284324   .0500531    -0.57   0.570    -.1267974    .0699327
treat23_college |   .0218463   .0548131     0.40   0.690    -.0858732    .1295659
treat24_college |   .0017996    .053764     0.03   0.973    -.1038583    .1074574
          trump |  -.3698948   .0571864    -6.47   0.000    -.4822784   -.2575111
          _cons |   .6967312   .0275587    25.28   0.000     .6425725      .75089
---------------------------------------------------------------------------------
(est3 stored)

. eststo  : reg immig_index treat22 treat23 treat24 college treat22_college treat23_college treat24_college trump female incomeR white rel college if rep == 0,
>  robust
note: college omitted because of collinearity

Linear regression                               Number of obs     =        462
                                                F(12, 449)        =       6.52
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1433
                                                Root MSE          =     .19601

---------------------------------------------------------------------------------
                |               Robust
    immig_index |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        treat22 |   .0372968   .0367412     1.02   0.311    -.0349093    .1095028
        treat23 |   .0486026   .0437498     1.11   0.267    -.0373773    .1345825
        treat24 |   .0242257    .042007     0.58   0.564     -.058329    .1067803
        college |   .0411684   .0370421     1.11   0.267    -.0316291    .1139658
treat22_college |   -.028685   .0493298    -0.58   0.561     -.125631     .068261
treat23_college |   .0079313    .055905     0.14   0.887    -.1019366    .1177992
treat24_college |  -.0067421   .0548779    -0.12   0.902    -.1145916    .1011074
          trump |  -.3656611   .0573264    -6.38   0.000    -.4783225   -.2529997
         female |  -.0333015   .0188443    -1.77   0.078    -.0703355    .0037325
        incomeR |   .0218808   .0439209     0.50   0.619    -.0644352    .1081969
          white |   .0194633   .0225145     0.86   0.388    -.0247836    .0637102
            rel |  -.0214275    .006717    -3.19   0.002    -.0346281    -.008227
        college |          0  (omitted)
          _cons |   .7017648   .0383614    18.29   0.000     .6263746    .7771549
---------------------------------------------------------------------------------
(est4 stored)

. esttab using college_moderator.tex, ar2 b(3) se(3) starlevels(* 0.1 ** .05 *** .01) label replace
(output written to college_moderator.tex)

. eststo clear

. 
. 
. 
. 
end of do-file

. 
. log close
      name:  <unnamed>
       log:  C:\Users\tabi\Dropbox\BOMO\JEPSReplication\FinalReplication\Final\log.log
  log type:  text
 closed on:  24 Jan 2018, 11:52:58
---------------------------------------------------------------------------------------------------------------------------------------------------------------
